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Zeitschriftenartikel zum Thema "Attention based models"
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Qin, Chu-Xiong, und Dan Qu. „Towards Understanding Attention-Based Speech Recognition Models“. IEEE Access 8 (2020): 24358–69. http://dx.doi.org/10.1109/access.2020.2970758.
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Steelman, Kelly S., Jason S. McCarley und Christopher D. Wickens. „Theory-based Models of Attention in Visual Workspaces“. International Journal of Human–Computer Interaction 33, Nr. 1 (16.09.2016): 35–43. http://dx.doi.org/10.1080/10447318.2016.1232228.
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Hashemi, Seyyed Mohammad Reza. „A Survey of Visual Attention Models“. Ciência e Natura 37 (19.12.2015): 297. http://dx.doi.org/10.5902/2179460x20786.
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The present paper surveys visual attention models, showing factors’ categorization. It also studies bottom-up models in comparison to top-to-down, spatial models compared to spatial-temporal ones, obvious attention against the hidden one, and space-based models against the object-based ones. It categorizes some challenging model issues, including biological calculations, correlation with the set of eye-movement data, as well as bottom-up and top-to-down topics, explaining each in details.
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Zhou, Qifeng, Xiang Liu und Qing Wang. „Interpretable duplicate question detection models based on attention mechanism“. Information Sciences 543 (Januar 2021): 259–72. http://dx.doi.org/10.1016/j.ins.2020.07.048.
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Kramer, Arthur F., und Andrew Jacobson. „A comparison of Space-Based and Object-Based Models of Visual Attention“. Proceedings of the Human Factors Society Annual Meeting 34, Nr. 19 (Oktober 1990): 1489–93. http://dx.doi.org/10.1177/154193129003401915.
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Wang, Lei, Ed X. Wu und Fei Chen. „EEG-based auditory attention decoding using speech-level-based segmented computational models“. Journal of Neural Engineering 18, Nr. 4 (25.05.2021): 046066. http://dx.doi.org/10.1088/1741-2552/abfeba.
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Rosenberg, Monica D., Wei-Ting Hsu, Dustin Scheinost, R. Todd Constable und Marvin M. Chun. „Connectome-based Models Predict Separable Components of Attention in Novel Individuals“. Journal of Cognitive Neuroscience 30, Nr. 2 (Februar 2018): 160–73. http://dx.doi.org/10.1162/jocn_a_01197.
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Although we typically talk about attention as a single process, it comprises multiple independent components. But what are these components, and how are they represented in the functional organization of the brain? To investigate whether long-studied components of attention are reflected in the brain's intrinsic functional organization, here we apply connectome-based predictive modeling (CPM) to predict the components of Posner and Petersen's influential model of attention: alerting (preparing and maintaining alertness and vigilance), orienting (directing attention to a stimulus), and executive control (detecting and resolving cognitive conflict) [Posner, M. I., & Petersen, S. E. The attention system of the human brain. Annual Review of Neuroscience, 13, 25–42, 1990]. Participants performed the Attention Network Task (ANT), which measures these three factors, and rested during fMRI scanning. CPMs tested with leave-one-subject-out cross-validation successfully predicted novel individual's overall ANT accuracy, RT variability, and executive control scores from functional connectivity observed during ANT performance. CPMs also generalized to predict participants' alerting scores from their resting-state functional connectivity alone, demonstrating that connectivity patterns observed in the absence of an explicit task contain a signature of the ability to prepare for an upcoming stimulus. Suggesting that significant variance in ANT performance is also explained by an overall sustained attention factor, the sustained attention CPM, a model defined in prior work to predict sustained attentional abilities, predicted accuracy, RT variability, and executive control from task-based data and predicted RT variability from resting-state data. Our results suggest that, whereas executive control may be closely related to sustained attention, the infrastructure that supports alerting is distinct and can be measured at rest. In the future, CPM may be applied to elucidate additional independent components of attention and relationships between the functional brain networks that predict them.
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Kristensen, Terje. „Towards Spike based Models of Visual Attention in the Brain“. International Journal of Adaptive, Resilient and Autonomic Systems 6, Nr. 2 (Juli 2015): 117–38. http://dx.doi.org/10.4018/ijaras.2015070106.
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A numerical solution of Hodgkin Huxley equations is presented to simulate the spiking behavior of a biological neuron. The solution is illustrated by building a graphical chart interface to finely tune the behavior of the neuron under different stimulations. In addition, a Multi-Agent System (MAS) has been developed to simulate the Visual Attention Network Model of the brain. Tasks are assigned to the agents according to the Attention Network Theory, developed by neuroscientists. A sequential communication model based on simple objects has been constructed, aiming to show the relations and the workflow between the different visual attention networks. Each agent is being used as an analogy to a role or function of the visual attention systems in the brain. Some experimental results based on this model have been presented in an earlier paper. The two approaches are at the moment not integrated. The long term goal is to develop an integrated parallel layered object model of the visual attention process, as a tool for simulating neuron interactions described by Hodgkin Huxley's equations or the Leaky-Integrate-and-Fire model.
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Tiawongsombat, Prasertsak, Mun-Ho Jeong, Alongkorn Pirayawaraporn, Joong-Jae Lee und Joo-Seop Yun. „Vision-Based Attentiveness Determination Using Scalable HMM Based on Relevance Theory“. Sensors 19, Nr. 23 (03.12.2019): 5331. http://dx.doi.org/10.3390/s19235331.
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Attention capability is an essential component of human–robot interaction. Several robot attention models have been proposed which aim to enable a robot to identify the attentiveness of the humans with which it communicates and gives them its attention accordingly. However, previous proposed models are often susceptible to noisy observations and result in the robot’s frequent and undesired shifts in attention. Furthermore, most approaches have difficulty adapting to change in the number of participants. To address these limitations, a novel attentiveness determination algorithm is proposed for determining the most attentive person, as well as prioritizing people based on attentiveness. The proposed algorithm, which is based on relevance theory, is named the Scalable Hidden Markov Model (Scalable HMM). The Scalable HMM allows effective computation and contributes an adaptation approach for human attentiveness; unlike conventional HMMs, Scalable HMM has a scalable number of states and observations and online adaptability for state transition probabilities, in terms of changes in the current number of states, i.e., the number of participants in a robot’s view. The proposed approach was successfully tested on image sequences (7567 frames) of individuals exhibiting a variety of actions (speaking, walking, turning head, and entering or leaving a robot’s view). From these experimental results, Scalable HMM showed a detection rate of 76% in determining the most attentive person and over 75% in prioritizing people’s attention with variation in the number of participants. Compared to recent attention approaches, Scalable HMM’s performance in people attention prioritization presents an approximately 20% improvement.
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Si, Nianwen, Wenlin Zhang, Dan Qu, Xiangyang Luo, Heyu Chang und Tong Niu. „Spatial-Channel Attention-Based Class Activation Mapping for Interpreting CNN-Based Image Classification Models“. Security and Communication Networks 2021 (31.05.2021): 1–13. http://dx.doi.org/10.1155/2021/6682293.
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Convolutional neural network (CNN) has been applied widely in various fields. However, it is always hindered by the unexplainable characteristics. Users cannot know why a CNN-based model produces certain recognition results, which is a vulnerability of CNN from the security perspective. To alleviate this problem, in this study, the three existing feature visualization methods of CNN are analyzed in detail firstly, and a unified visualization framework for interpreting the recognition results of CNN is presented. Here, class activation weight (CAW) is considered as the most important factor in the framework. Then, the different types of CAWs are further analyzed, and it is concluded that a linear correlation exists between them. Finally, on this basis, a spatial-channel attention-based class activation mapping (SCA-CAM) method is proposed. This method uses different types of CAWs as attention weights and combines spatial and channel attentions to generate class activation maps, which is capable of using richer features for interpreting the results of CNN. Experiments on four different networks are conducted. The results verify the linear correlation between different CAWs. In addition, compared with the existing methods, the proposed method SCA-CAM can effectively improve the visualization effect of the class activation map with higher flexibility on network structure.
Dissertationen zum Thema "Attention based models"
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Belkacem, Thiziri. „Neural models for information retrieval : towards asymmetry sensitive approaches based on attention models“. Thesis, Toulouse 3, 2019. http://www.theses.fr/2019TOU30167.
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Ce travail se situe dans le contexte de la recherche d'information (RI) utilisant des techniques d'intelligence artificielle (IA) telles que l'apprentissage profond (DL). Il s'intéresse à des tâches nécessitant l'appariement de textes, telles que la recherche ad-hoc, le domaine du questions-réponses et l'identification des paraphrases. L'objectif de cette thèse est de proposer de nouveaux modèles, utilisant les méthodes de DL, pour construire des modèles d'appariement basés sur la sémantique de textes, et permettant de pallier les problèmes de l'inadéquation du vocabulaire relatifs aux représentations par sac de mots, ou bag of words (BoW), utilisées dans les modèles classiques de RI. En effet, les méthodes classiques de comparaison de textes sont basées sur la représentation BoW qui considère un texte donné comme un ensemble de mots indépendants. Le processus d'appariement de deux séquences de texte repose sur l'appariement exact entre les mots. La principale limite de cette approche est l'inadéquation du vocabulaire. Ce problème apparaît lorsque les séquences de texte à apparier n'utilisent pas le même vocabulaire, même si leurs sujets sont liés. Par exemple, la requête peut contenir plusieurs mots qui ne sont pas nécessairement utilisés dans les documents de la collection, notamment dans les documents pertinents. Les représentations BoW ignorent plusieurs aspects, tels que la structure du texte et le contexte des mots. Ces caractéristiques sont très importantes et permettent de différencier deux textes utilisant les mêmes mots et dont les informations exprimées sont différentes. Un autre problème dans l'appariement de texte est lié à la longueur des documents. Les parties pertinentes peuvent être réparties de manières différentes dans les documents d'une collection. Ceci est d'autant vrai dans les documents volumineux qui ont tendance à couvrir un grand nombre de sujets et à inclure un vocabulaire variable. Un document long pourrait ainsi comporter plusieurs passages pertinents qu'un modèle d'appariement doit capturer. Contrairement aux documents longs, les documents courts sont susceptibles de concerner un sujet spécifique et ont tendance à contenir un vocabulaire plus restreint. L'évaluation de leur pertinence est en principe plus simple que celle des documents plus longs. Dans cette thèse, nous avons proposé différentes contributions répondant chacune à l'un des problèmes susmentionnés. Tout d'abord, afin de résoudre le problème d'inadéquation du vocabulaire, nous avons utilisé des représentations distribuées des mots (plongement lexical) pour permettre un appariement basé sur la sémantique entre les différents mots. Ces représentations ont été utilisées dans des applications de RI où la similarité document-requête est calculée en comparant tous les vecteurs de termes de la requête avec tous les vecteurs de termes du document, indifféremment. Contrairement aux modèles proposés dans l'état-de-l'art, nous avons étudié l'impact des termes de la requête concernant leur présence/absence dans un document. Nous avons adopté différentes stratégies d'appariement document/requête. L'intuition est que l'absence des termes de la requête dans les documents pertinents est en soi un aspect utile à prendre en compte dans le processus de comparaison. En effet, ces termes n'apparaissent pas dans les documents de la collection pour deux raisons possibles : soit leurs synonymes ont été utilisés ; soit ils ne font pas partie du contexte des documents en questionsThis work is situated in the context of information retrieval (IR) using machine learning (ML) and deep learning (DL) techniques. It concerns different tasks requiring text matching, such as ad-hoc research, question answering and paraphrase identification. The objective of this thesis is to propose new approaches, using DL methods, to construct semantic-based models for text matching, and to overcome the problems of vocabulary mismatch related to the classical bag of word (BoW) representations used in traditional IR models. Indeed, traditional text matching methods are based on the BoW representation, which considers a given text as a set of independent words. The process of matching two sequences of text is based on the exact matching between words. The main limitation of this approach is related to the vocabulary mismatch. This problem occurs when the text sequences to be matched do not use the same vocabulary, even if their subjects are related. For example, the query may contain several words that are not necessarily used in the documents of the collection, including relevant documents. BoW representations ignore several aspects about a text sequence, such as the structure the context of words. These characteristics are important and make it possible to differentiate between two texts that use the same words but expressing different information. Another problem in text matching is related to the length of documents. The relevant parts can be distributed in different ways in the documents of a collection. This is especially true in large documents that tend to cover a large number of topics and include variable vocabulary. A long document could thus contain several relevant passages that a matching model must capture. Unlike long documents, short documents are likely to be relevant to a specific subject and tend to contain a more restricted vocabulary. Assessing their relevance is in principle simpler than assessing the one of longer documents. In this thesis, we have proposed different contributions, each addressing one of the above-mentioned issues. First, in order to solve the problem of vocabulary mismatch, we used distributed representations of words (word embedding) to allow a semantic matching between the different words. These representations have been used in IR applications where document/query similarity is computed by comparing all the term vectors of the query with all the term vectors of the document, regardless. Unlike the models proposed in the state-of-the-art, we studied the impact of query terms regarding their presence/absence in a document. We have adopted different document/query matching strategies. The intuition is that the absence of the query terms in the relevant documents is in itself a useful aspect to be taken into account in the matching process. Indeed, these terms do not appear in documents of the collection for two possible reasons: either their synonyms have been used or they are not part of the context of the considered documents. The methods we have proposed make it possible, on the one hand, to perform an inaccurate matching between the document and the query, and on the other hand, to evaluate the impact of the different terms of a query in the matching process. Although the use of word embedding allows semantic-based matching between different text sequences, these representations combined with classical matching models still consider the text as a list of independent elements (bag of vectors instead of bag of words). However, the structure of the text as well as the order of the words is important. Any change in the structure of the text and/or the order of words alters the information expressed. In order to solve this problem, neural models were used in text matching
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Saifullah, Mohammad. „Biologically-Based Interactive Neural Network Models for Visual Attention and Object Recognition“. Doctoral thesis, Linköpings universitet, Institutionen för datavetenskap, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-79336.
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The main focus of this thesis is to develop biologically-based computational models for object recognition. A series of models for attention and object recognition were developed in the order of increasing functionality and complexity. These models are based on information processing in the primate brain, and specially inspired from the theory of visual information processing along the two parallel processing pathways of the primate visual cortex. To capture the true essence of incremental, constraint satisfaction style processing in the visual system, interactive neural networks were used for implementing our models. Results from eye-tracking studies on the relevant visual tasks, as well as our hypothesis regarding the information processing in the primate visual system, were implemented in the models and tested with simulations. As a first step, a model based on the ventral pathway was developed to recognize single objects. Through systematic testing, structural and algorithmic parameters of these models were fine tuned for performing their task optimally. In the second step, the model was extended by considering the dorsal pathway, which enables simulation of visual attention as an emergent phenomenon. The extended model was then investigated for visual search tasks. In the last step, we focussed on occluded and overlapped object recognition. A couple of eye-tracking studies were conducted in this regard and on the basis of the results we made some hypotheses regarding information processing in the primate visual system. The models were further advanced on the lines of the presented hypothesis, and simulated on the tasks of occluded and overlapped object recognition. On the basis of the results and analysis of our simulations we have further found that the generalization performance of interactive hierarchical networks improves with the addition of a small amount of Hebbian learning to an otherwise pure error-driven learning. We also concluded that the size of the receptive fields in our networks is an important parameter for the generalization task and depends on the object of interest in the image. Our results show that networks using hard coded feature extraction perform better than the networks that use Hebbian learning for developing feature detectors. We have successfully demonstrated the emergence of visual attention within an interactive network and also the role of context in the search task. Simulation results with occluded and overlapped objects support our extended interactive processing approach, which is a combination of the interactive and top-down approach, to the segmentation-recognition issue. Furthermore, the simulation behavior of our models is in line with known human behavior for similar tasks. In general, the work in this thesis will improve the understanding and performance of biologically-based interactive networks for object recognition and provide a biologically-plausible solution to recognition of occluded and overlapped objects. Moreover, our models provide some suggestions for the underlying neural mechanism and strategies behind biological object recognition.
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Borba, Gustavo Benvenutti. „Automatic extraction of regions of interest from images based on visual attention models“. Universidade Tecnológica Federal do Paraná, 2010. http://repositorio.utfpr.edu.br/jspui/handle/1/1295.
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UOL; CAPESEsta tese apresenta um método para a extração de regiões de interesse (ROIs) de imagens. No contexto deste trabalho, ROIs são definidas como os objetos semânticos que se destacam em uma imagem, podendo apresentar qualquer tamanho ou localização. O novo método baseia-se em modelos computacionais de atenção visual (VA), opera de forma completamente bottom-up, não supervisionada e não apresenta restrições com relação à categoria da imagem de entrada. Os elementos centrais da arquitetura são os modelos de VA propostos por Itti-Koch-Niebur e Stentiford. O modelo de Itti-Koch-Niebur considera as características de cor, intensidade e orientação da imagem e apresenta uma resposta na forma de coordenadas, correspondentes aos pontos de atenção (POAs) da imagem. O modelo Stentiford considera apenas as características de cor e apresenta a resposta na forma de áreas de atenção na imagem (AOAs). Na arquitetura proposta, a combinação de POAs e AOAs permite a obtenção dos contornos das ROIs. Duas implementações desta arquitetura, denominadas 'primeira versão' e 'versão melhorada' são apresentadas. A primeira versão utiliza principalmente operações tradicionais de morfologia matemática. Esta versão foi aplicada em dois sistemas de recuperação de imagens com base em regiões. No primeiro, as imagens são agrupadas de acordo com as ROIs, ao invés das características globais da imagem. O resultado são grupos de imagens mais significativos semanticamente, uma vez que o critério utilizado são os objetos da mesma categoria contidos nas imagens. No segundo sistema, á apresentada uma combinação da busca de imagens tradicional, baseada nas características globais da imagem, com a busca de imagens baseada em regiões. Ainda neste sistema, as buscas são especificadas através de mais de uma imagem exemplo. Na versão melhorada da arquitetura, os estágios principais são uma análise de coerência espacial entre as representações de ambos modelos de VA e uma representação multi-escala das AOAs. Se comparada à primeira versão, esta apresenta maior versatilidade, especialmente com relação aos tamanhos das ROIs presentes nas imagens. A versão melhorada foi avaliada diretamente, com uma ampla variedade de imagens diferentes bancos de imagens públicos, com padrões-ouro na forma de bounding boxes e de contornos reais dos objetos. As métricas utilizadas na avaliação foram presision, recall, F1 e area of overlap. Os resultados finais são excelentes, considerando-se a abordagem exclusivamente bottom-up e não-supervisionada do método.
This thesis presents a method for the extraction of regions of interest (ROIs) from images. By ROIs we mean the most prominent semantic objects in the images, of any size and located at any position in the image. The novel method is based on computational models of visual attention (VA), operates under a completely bottom-up and unsupervised way and does not present con-straints in the category of the input images. At the core of the architecture is de model VA proposed by Itti, Koch and Niebur and the one proposed by Stentiford. The first model takes into account color, intensity, and orientation features and provides coordinates corresponding to the points of attention (POAs) in the image. The second model considers color features and provides rough areas of attention (AOAs) in the image. In the proposed architecture, the POAs and AOAs are combined to establish the contours of the ROIs. Two implementations of this architecture are presented, namely 'first version' and 'improved version'. The first version mainly on traditional morphological operations and was applied in two novel region-based image retrieval systems. In the first one, images are clustered on the basis of the ROIs, instead of the global characteristics of the image. This provides a meaningful organization of the database images, since the output clusters tend to contain objects belonging to the same category. In the second system, we present a combination of the traditional global-based with region-based image retrieval under a multiple-example query scheme. In the improved version of the architecture, the main stages are a spatial coherence analysis between both VA models and a multiscale representation of the AOAs. Comparing to the first one, the improved version presents more versatility, mainly in terms of the size of the extracted ROIs. The improved version was directly evaluated for a wide variety of images from different publicly available databases, with ground truth in the form of bounding boxes and true object contours. The performance measures used were precision, recall, F1 and area overlap. Experimental results are of very high quality, particularly if one takes into account the bottom-up and unsupervised nature of the approach.
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Kliegl, Reinhold, Ping Wei, Michael Dambacher, Ming Yan und Xiaolin Zhou. „Experimental effects and individual differences in linear mixed models: Estimating the relationship between spatial, object, and attraction effects in visual attention“. Universität Potsdam, 2011. http://opus.kobv.de/ubp/volltexte/2011/5685/.
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Linear mixed models (LMMs) provide a still underused methodological perspective on combining experimental and individual-differences research. Here we illustrate this approach with two-rectangle cueing in visual attention (Egly et al., 1994). We replicated previous experimental cue-validity effects relating to a spatial shift of attention within an object (spatial effect), to attention switch between objects (object effect), and to the attraction of attention toward the display centroid (attraction effect), also taking into account the design-inherent imbalance of valid and other trials. We simultaneously estimated variance/covariance components of subject-related random effects for these spatial, object, and attraction effects in addition to their mean reaction times (RTs). The spatial effect showed a strong positive correlation with mean RT and a strong negative correlation with the attraction effect. The analysis of individual differences suggests that slow subjects engage attention more strongly at the cued location than fast subjects. We compare this joint LMM analysis of experimental effects and associated subject-related variances and correlations with two frequently used alternative statistical procedures
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Dimitriadis, Spyridon. „Multi-task regression QSAR/QSPR prediction utilizing text-based Transformer Neural Network and single-task using feature-based models“. Thesis, Linköpings universitet, Statistik och maskininlärning, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-177186.
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With the recent advantages of machine learning in cheminformatics, the drug discovery process has been accelerated; providing a high impact in the field of medicine and public health. Molecular property and activity prediction are key elements in the early stages of drug discovery by helping prioritize the experiments and reduce the experimental work. In this thesis, a novel approach for multi-task regression using a text-based Transformer model is introduced and thoroughly explored for training on a number of properties or activities simultaneously. This multi-task regression with Transformer based model is inspired by the field of Natural Language Processing (NLP) which uses prefix tokens to distinguish between each task. In order to investigate our architecture two data categories are used; 133 biological activities from ExCAPE database and three physical chemistry properties from MoleculeNet benchmark datasets. The Transformer model consists of the embedding layer with positional encoding, a number of encoder layers, and a Feedforward Neural Network (FNN) to turn it into a regression problem. The molecules are represented as a string of characters using the Simplified Molecular-Input Line-Entry System (SMILES) which is a ’chemistry language’ with its own syntax. In addition, the effect of Transfer Learning is explored by experimenting with two pretrained Transformer models, pretrained on 1.5 million and on 100 million molecules. The text-base Transformer models are compared with a feature-based Support Vector Regression (SVR) with the Tanimoto kernel where the input molecules are encoded as Extended Connectivity Fingerprint (ECFP), which are calculated features. The results have shown that Transfer Learning is crucial for improving the performance on both property and activity predictions. On bioactivity tasks, the larger pretrained Transformer on 100 million molecules achieved comparable performance to the feature-based SVR model; however, overall SVR performed better on the majority of the bioactivity tasks. On the other hand, on physicochemistry property tasks, the larger pretrained Transformer outperformed SVR on all three tasks. Concluding, the multi-task regression architecture with the prefix token had comparable performance with the traditional feature-based approach on predicting different molecular properties or activities. Lastly, using the larger pretrained models trained on a wide chemical space can play a key role in improving the performance of Transformer models on these tasks.
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Holmström, Oskar. „Exploring Transformer-Based Contextual Knowledge Graph Embeddings : How the Design of the Attention Mask and the Input Structure Affect Learning in Transformer Models“. Thesis, Linköpings universitet, Artificiell intelligens och integrerade datorsystem, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-175400.
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The availability and use of knowledge graphs have become commonplace as a compact storage of information and for lookup of facts. However, the discrete representation makes the knowledge graph unavailable for tasks that need a continuous representation, such as predicting relationships between entities, where the most probable relationship needs to be found. The need for a continuous representation has spurred the development of knowledge graph embeddings. The idea is to position the entities of the graph relative to each other in a continuous low-dimensional vector space, so that their relationships are preserved, and ideally leading to clusters of entities with similar characteristics. Several methods to produce knowledge graph embeddings have been created, from simple models that minimize the distance between related entities to complex neural models. Almost all of these embedding methods attempt to create an accurate static representation of each entity and relation. However, as with words in natural language, both entities and relations in a knowledge graph hold different meanings in different local contexts. With the recent development of Transformer models, and their success in creating contextual representations of natural language, work has been done to apply them to graphs. Initial results show great promise, but there are significant differences in archi- tecture design across papers. There is no clear direction on how Transformer models can be best applied to create contextual knowledge graph embeddings. Two of the main differences in previous work is how the attention mask is applied in the model and what input graph structures the model is trained on. This report explores how different attention masking methods and graph inputs affect a Transformer model (in this report, BERT) on a link prediction task for triples. Models are trained with five different attention masking methods, which to varying degrees restrict attention, and on three different input graph structures (triples, paths, and interconnected triples). The results indicate that a Transformer model trained with a masked language model objective has the strongest performance on the link prediction task when there are no restrictions on how attention is directed, and when it is trained on graph structures that are sequential. This is similar to how models like BERT learn sentence structure after being exposed to a large number of training samples. For more complex graph structures it is beneficial to encode information of the graph structure through how the attention mask is applied. There also seems to be some indications that the input graph structure affects the models’ capabilities to learn underlying characteristics in the knowledge graph that is trained upon.
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Klamser, Pascal. „Collective Information Processing and Criticality, Evolution and Limited Attention“. Doctoral thesis, Humboldt-Universität zu Berlin, 2021. http://dx.doi.org/10.18452/23099.
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Im ersten Teil analysiere ich die Selbstorganisation zur Kritikalität (hier ein Phasenübergang von Ordnung zu Unordnung) und untersuche, ob Evolution ein möglicher Organisationsmechanismus ist.
Die Kernfrage ist, ob sich ein simulierter kohäsiver Schwarm, der versucht, einem Raubtier auszuweichen, durch Evolution selbst zum kritischen Punkt entwickelt, um das Ausweichen zu optimieren?
Es stellt sich heraus, dass (i) die Gruppe den Jäger am besten am kritischen Punkt vermeidet, aber (ii) nicht durch einer verstärkten Reaktion, sondern durch strukturelle Veränderungen, (iii) das Gruppenoptimum ist evolutionär unstabiler aufgrund einer maximalen räumlichen Selbstsortierung der Individuen.
Im zweiten Teil modelliere ich experimentell beobachtete Unterschiede im kollektiven Verhalten von Fischgruppen, die über mehrere Generationen verschiedenen Arten von größenabhängiger Selektion ausgesetzt waren.
Diese Größenselektion soll Freizeitfischerei (kleine Fische werden freigelassen, große werden konsumiert) und die kommerzielle Fischerei mit großen Netzbreiten (kleine/junge Individuen können entkommen) nachahmen.
Die zeigt sich, dass das Fangen großer Fische den Zusammenhalt und die Risikobereitschaft der Individuen reduziert.
Beide Befunde lassen sich mechanistisch durch einen Aufmerksamkeits-Kompromiss zwischen Sozial- und Umweltinformationen erklären.
Im letzten Teil der Arbeit quantifiziere ich die kollektive Informationsverarbeitung im Feld.
Das Studiensystem ist eine an sulfidische Wasserbedingungen angepasste Fischart mit einem kollektiven Fluchtverhalten vor Vögeln (wiederholte kollektive Fluchttauchgängen).
Die Fische sind etwa 2 Zentimeter groß, aber die kollektive Welle breitet sich über Meter in dichten Schwärmen an der Oberfläche aus.
Es zeigt sich, dass die Wellengeschwindigkeit schwach mit der Polarisation zunimmt, bei einer optimalen Dichte am schnellsten ist und von ihrer Richtung relativ zur Schwarmorientierung abhängt.In the first part, I focus on the self-organization to criticality (here an order-disorder phase transition) and investigate if evolution is a possible self-tuning mechanism. Does a simulated cohesive swarm that tries to avoid a pursuing predator self-tunes itself by evolution to the critical point to optimize avoidance? It turns out that (i) the best group avoidance is at criticality but (ii) not due to an enhanced response but because of structural changes (fundamentally linked to criticality), (iii) the group optimum is not an evolutionary stable state, in fact (iv) it is an evolutionary accelerator due to a maximal spatial self-sorting of individuals causing spatial selection. In the second part, I model experimentally observed differences in collective behavior of fish groups subject to multiple generation of different types of size-dependent selection. The real world analog to this experimental evolution is recreational fishery (small fish are released, large are consumed) and commercial fishing with large net widths (small/young individuals can escape). The results suggest that large harvesting reduces cohesion and risk taking of individuals. I show that both findings can be mechanistically explained based on an attention trade-off between social and environmental information. Furthermore, I numerically analyze how differently size-harvested groups perform in a natural predator and fishing scenario. In the last part of the thesis, I quantify the collective information processing in the field. The study system is a fish species adapted to sulfidic water conditions with a collective escape behavior from aerial predators which manifests in repeated collective escape dives. These fish measure about 2 centimeters, but the collective wave spreads across meters in dense shoals at the surface. I find that wave speed increases weakly with polarization, is fastest at an optimal density and depends on its direction relative to shoal orientation.
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Wennerholm, Pia. „The Role of High-Level Reasoning and Rule-Based Representations in the Inverse Base-Rate Effect“. Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis : Universitetsbiblioteket [distributör], 2001. http://publications.uu.se/theses/91-554-5178-0/.
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Desai, Anver. „Policy agenda-setting and the use of analytical agenda-setting models for school sport and physical education in South Africa“. Thesis, University of the Western Cape, 2011. http://hdl.handle.net/11394/3596.
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This study focused on policy agenda-setting models for school sport and physical education in South Africa. The primary objective was to assess and propose options for improved agenda-setting by focussing on the use of agenda-setting models and by applying it to physical education and school sport and the policy agenda of the national government. The study has shown that pertinent school sport and physical education policy issues, as supported by key role-players and principal actors, were initially not placed on the formal policy agenda of government during the research investigation period (2005-2009). However, during 2010 and 2011 the issue of school sport and physical education received prominent attention by authorities and these developments were subsequently included in the study. The study aimed at contributing to existing policy agenda-setting models and by recommending changes to the Generic Process Model.The study also made a contribution by informing various role-players and stakeholders in education and school sport on the opportunities in policy agenda-setting. The study showed that policy agenda-setting is a vital step in the Generic Policy Process Model. Policy agendasetting in South Africa is critical, as it is important to place new and emerging policy issues on the policy agenda and as a participative public policy process is relatively new in this young democracy. The reader should not confuse the study as one dealing with school sport and physical education primarily, but rather as a research investigation dealing with policy agenda-setting models as applied to school sport and physical education.The secondary objectives of the study included the development of a historical perspective on trends and tendencies in education and sport in South Africa. A second objective was to provide theoretical perspectives on public policy and specifically on policy agenda-setting. From these theoretical perspectives, the Generic Policy Process Model was selected to use as a model that provided guidance on the overall policy process normally followed in South Africa. The Issue Attention Cycle and Principal Actor Models on Agenda-Setting were selected to apply to the case study to specifically ascertain important factors related to policy agenda-setting such as the identification of key role players as well as key policy issues. The Generic Policy Process Model provided for both a comprehensive set of phases as well as specific requirements and key issues to be addressed during each phase of the policy process.In terms of findings the study found that a number of specific agenda-setting elements or phases needed to be added to the Generic Policy Process Model, which includes a problem stage, triggers, initiator, issue creation and actors or policy stakeholders.The Principal Actor Model to agenda-setting was selected for application to the case as different actors have different levels of success at each policy stage. In the South African experience it is important to look at who sets the policy agenda and why, who can initiate agenda-setting and the role played by these principal actors in the agenda-setting process.Issue emergence often places policy issues on the policy agenda. The public is initially involved in issues, but in the long term public interest declines. The government realizes the significant costs involved in placing policy issues back on the agenda. This leads to a decline in issue attention by policy-makers and the public. The Issue Attention Cycle Model of
agenda setting was used to analyse this phenomenon in South African Education policy.The study provides a case assessment of the South African experience. From the research findings, a set of conclusions and recommendations were developed for improved policy agenda-setting models and implications for school sport and physical education, as well as tools to place it on the national policy agenda were identified. The research findings suggest that pertinent school sport and physical education policy issues, as supported by key roleplayers,stakeholders and principal actors were not placed on the formal policy agenda of the government as a vital step in the policy process between 2005 and 2009. Ever since, principal policy actors, civil society NGOs, and government officials placed sufficient pressure on the Minister of Basic Education to place Physical Education on the agenda. Subsequently,Minister Angie Motshega has placed physical education in the school Curriculum under the subject Life Orientation and Lifeskills. It has become evident from the research that agendasetting is both necessary to, and a complex phase in, the policy-making process.This study has shown that major policy issues such as physical education and school sport were neglected during the period 2005 and 2009 despite reformed and advanced policy cycles in government. It has also shown that the role of policy agenda-setting in the overall policymaking
process was revisited by government in the subsequent period 2010/2011 and placed on the policy agenda. Specific lessons of experience emanated from this process.The study recommends that the triggers of the agenda-setting phases be added to the Generic Policy Process Model, which should include the problem stage, triggers, initiators, issue creation, actors and policy stakeholders. Principal actors in the agenda-setting model in South Africa want the issue of physical education and school sport to be part of the school curriculum, and therefore be placed back on the policy agenda by the Government on its institutional agenda. Furthermore, the study showed that actors wanted it to be compulsory in all phases of the school (Foundation, Intermediate, Senior, GET, FET) and that it should have the same legal status as other subjects.The important findings include that: Comprehensive policy process models such as that of Dunn, Wissink and the Generic Process model may need to be reviewed to incorporate more fully the policy-agenda
setting stages of the overall process; Current policy agenda setting models in use are relevant and valuable in identifying key role players as well as key issues and considerations regarding the policy process; Institutional arrangements to strengthen the role of NGOs and lower level institutions,such as schools to participate in policy agenda setting are important; and the study has shown that a number of key factors have been identified that had a key influence on policy agenda-setting in the case of physical education and school sport in South Africa. These included the influence of changing political leadership, the competency of policy capacities in government, the profile of issues in the media etc. The key findings of the study have shown that further potential exists to improve
monitoring and evaluation and policy analysis.The study made a set of recommendations to principal actors such as the Minister of Education, Minister of Sport and Recreation, non-governmental organisations, interest groups,department officials and pressure groups. A set of research topics was also identified
for future research.Philosophiae Doctor - PhD
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Ungruh, Joachim. „A neurally based vision model for line extraction and attention“. Thesis, Georgia Institute of Technology, 1992. http://hdl.handle.net/1853/8303.
Der volle Inhalt der QuelleBücher zum Thema "Attention based models"
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Sokol'skaya, Elena, und Boris Kochurov. Geoecology of the city: models of environmental quality. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1205961.
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The monograph examines the features of studying the geoecological state of urbanized territories, reveals the use of integrated assessment and mapping in urban diagnostics, and finds a solution to geoecological problems on the example of world cities that are leading in the rating for quality of life.
The components of an information and analytical model of the urban environment for assessing the geoecological situation are described; an algorithm for a comprehensive study of the geoecological state aimed at an adequate assessment of the quality of the urban environment. Special attention is paid to the methodology of geoecological assessment of the quality of the urban environment based on multifactor modeling, which allows making recommendations for improving the comfort of living of the population.
It is intended for a wide range of specialists in the field of geoecology of the city, and can also be used as a textbook for students of environmental, natural-geographical, engineering specialties.
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Odincov, Boris. Models and intelligent systems. ru: INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1060845.
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The monograph consists of three chapters, the first of which outlines the theoretical foundations of intelligent information systems. Special attention is paid to the disclosure of the term "model" as the intended meaning depends on the understanding of the material. Introduces and examines the new concepts such as the associative and intuitive knowledge while in the creation of intellectual information systems are not used.
The second Chapter contains the analysis of problems of development of artificial intelligence (AI), developed in two directions: classical and statistical. Discusses difficulties in the development of the classical approach, associated with identifying the meaning of words, phrases, text, and formulating thoughts. The analysis of problems arising in the play of imagination and insight, machine understanding of natural language texts, play, verbalization and reflection.
The third Chapter contains examples of the development of intelligent information systems and technologies in practice of management of economic objects. Theoretical bases of construction of information robots designed to support the task hierarchy of the knowledge base and generating control regulations. The technology of their creation and application in the management of the business efficiency of enterprise business processes and its investment activities.
Focused on researchers and developers, AI and intelligent information systems, as well as graduate students and faculty in related academic disciplines.
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Babeshko, Lyudmila, und Irina Orlova. Econometrics and econometric modeling in Excel and R. ru: INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1079837.
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The textbook includes topics of modern econometrics, often used in economic research. Some aspects of multiple regression models related to the problem of multicollinearity and models with a discrete dependent variable are considered, including methods for their estimation, analysis, and application. A significant place is given to the analysis of models of one-dimensional and multidimensional time series. Modern ideas about the deterministic and stochastic nature of the trend are considered. Methods of statistical identification of the trend type are studied. Attention is paid to the evaluation, analysis, and practical implementation of Box — Jenkins stationary time series models, as well as multidimensional time series models: vector autoregressive models and vector error correction models. It includes basic econometric models for panel data that have been widely used in recent decades, as well as formal tests for selecting models based on their hierarchical structure. Each section provides examples of evaluating, analyzing, and testing models in the R software environment. Meets the requirements of the Federal state educational standards of higher education of the latest generation.
It is addressed to master's students studying in the Field of Economics, the curriculum of which includes the disciplines Econometrics (advanced course)", "Econometric modeling", "Econometric research", and graduate students."
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Vavrenyuk, Aleksandr, Viktor Makarov und Stanislav Kutepov. Operating systems. UNIX bases. ru: INFRA-M Academic Publishing LLC., 2016. http://dx.doi.org/10.12737/11186.
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In the manual basics command interfey-are covered
са operating systems of UNIX family. Much attention is paid
to practical use of teams of system and opportunities of language
programming, shell provided by a cover. In a grant vklyu-
Chena also some sections devoted to bases administrirova-
niya and to network means of OS. At the end of each section there are questions
for self-checking, the appendix contains a large number at -
mayors of writing of shell-procedures.
The manual is addressed to the students studying the modern
information technologies according to programs of a bachelor degree, and also all,
who wants to master the OS command interface of family independently
UNIX in the shortest possible time.
The edition can also be used as the short reference book on wasps -
new UNIX OS.
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Naumov, Vladimir. Consumer behavior. ru: INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1014653.
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The book describes the basic issues concerning consumer behavior on the basis of the simulation of the decision-making process on buying behavior of customers in the sales area of the store and shopping Internet sites.
The classification of models of consumer behavior, based on research in the area of economic, social and psychological theories and empirical evidence regarding decision-making by consumers when purchasing the goods, including online stores. Methods of qualitative and quantitative research of consumer behavior, fundamentals of statistical processing of empirical data.
Attention is paid to the processes of consumers ' perception of brands (brands) and advertising messages, the basic rules for the display of goods (merchandising) and its impact on consumer decision, recommendations on the use of psychology of consumer behavior in personal sales.
Presents an integrated model of consumer behavior in the Internet environment, the process of perception of the visitor of the company, the factors influencing consumer choice of goods online.
Is intended for preparation of bachelors in directions of preparation 38.03.02 "Management", 38.03.06 "trading business" and can be used for training of bachelors in direction of training 43.03.01 "Service", and will also be useful for professionals working in the field of marketing, distribution and sales.
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Sazhina, Muza. Management of economic crises: problems of theory and practice. ru: INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1111365.
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The monograph reveals the possibility and necessity of managing economic crises based on the analysis of the crisis as a form of movement of market processes. The article shows the virtualization of modern Finance, its separation from real production, its transformation into a self-sufficient element of the economy, the emergence of special financial crises in the global world and their negative impact on the real economy. Materials of modern financial and economic crises in different countries of the world economy are used. Special attention is paid to the specifics of crisis processes in Russia and the formation of their management practices.
It is intended for students and postgraduates of the faculty of public administration of the Lomonosov Moscow state University, as well as anyone interested in the problems of managing modern economic crises.
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Hmara, Ivan, und Viktor Strel'nikov. Environmental epidemiology and risk assessment. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1019063.
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The material presented in the textbook is based on modern ideas about environmental epidemiology as an interdisciplinary field of knowledge, the purpose of which is a multi — level study of the "environment-human health"system. Special attention is paid to the issues of risk assessment as an integral part of ecoepidemiological research. It corresponds to the program of the discipline "Environmental Epidemiology", approved by the Scientific and Methodological Council for Environmental Education of UMO Universities. For students in the field of training 05.03.06 "Ecology and nature management", as well as related biological, environmental and medical areas and specialists of the relevant work profiles.
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Kanke, Viktor. History of Philosophy. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/929952.
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The textbook is a sequential course in the history of philosophy. The history of philosophical innovations from antiquity to the present day is considered. The content of the philosophy of Antiquity, the Middle Ages, the Renaissance, Modern times, and the XIX century is presented. Special attention is paid to the main philosophical trends of the twentieth century, as well as Russian philosophy, including the Soviet period. The course is based on the achievements of modern science, as well as analytical philosophy, phenomenology, hermeneutics, poststructuralism and other major philosophical trends of our time. The theory of conceptual transduction is used. It is intended for bachelors studying in the enlarged group of training areas 47.00.00 "Philosophy, Ethics and Religious Studies" and other training areas. It is of considerable interest to a wide range of readers interested in the development of philosophical knowledge.
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Krivoyekov, Syergyey, und Roman Ayzman. Psychophysiology. ru: INFRA-M Academic Publishing LLC., 2015. http://dx.doi.org/10.12737/10884.
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Psychophysiology — the science studying interrelation of mentality of the person and physiological processes. Fundamental knowledge of work of a brain, first of all, of nervous regulation of functions of an organism, the general and specific features of the highest falls within the scope of its interests
nervous activity, the defining character and behavior of the person,
psychophysiological mechanisms of regulation of functional states.
In the book neurophysiological bases of coding and information processing in nervous system, neural mechanisms of feelings, perceptions, memories, training, motivations and emotions, thinking and the speech, attention, consciousness, behavior, mental activity are stated. Separate
the section is devoted to physiological bases of mental changes at various functional, extreme and pathophysiological states (a stress, post-stressful frustration, addiktivny states, depressions, etc.) and to ways of their correction. Authors tried to pay special attention to disclosure of specifics of psychophysiology of the person,
to difference of physiological mechanisms of regulation of mental functions of the person in comparison with model researches on animals.
For simplification of work on discipline and the best digestion of material
the textbook is supplied with the glossary.
For students, undergraduates, graduate students and teachers of psychological and medical faculties of higher education institutions.
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Ksenofontov, Boris, Gennadiy Pavlihin und Elena Simakova. Industrial ecology. ru: INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1017514.
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The basic issues of industrial ecology standards environmental quality, pollution of air and water basins, as well as waste production and possible sources of noise, vibration and electromagnetic radiation.
Provides information about the main methods and devices of protection of the environment from various contaminants, special attention is paid to those which are most commonly used in practice. The principles of developing environmentally friendly technologies and industries based on sustainable use of natural resources and conservation, as well as examples of creation of industrial facilities that have minimal impact on the environment. Much attention is paid to ecological expertise, which is one of the most important ways of identifying environmentally unsound technologies used in various industries.
Meets the requirements of Federal state educational standards of higher education of the last generation.
Is intended for preparation of bachelors in all areas of educational technology and technology in the study of professional discipline "life Safety" (module "environment Protection"), and can also be used by students of the faculty training of specialists in various industries.
Buchteile zum Thema "Attention based models"
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Hommel, Sebastian, Ahmad Rabie und Uwe Handmann. „Attention and Emotion Based Adaption of Dialog Systems“. In Intelligent Systems: Models and Applications, 215–35. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-33959-2_12.
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Milanova, Mariofanna, und Engin Mendi. „Attention in Image Sequences: Biology, Computational Models, and Applications“. In Advances in Reasoning-Based Image Processing Intelligent Systems, 147–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-24693-7_6.
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Roussinov, Dmitri, Serge Sharoff und Nadezhda Puchnina. „Recognizing Semantic Relations: Attention-Based Transformers vs. Recurrent Models“. In Lecture Notes in Computer Science, 561–74. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-45439-5_37.
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Gajbhiye, Amit, Thomas Winterbottom, Noura Al Moubayed und Steven Bradley. „Bilinear Fusion of Commonsense Knowledge with Attention-Based NLI Models“. In Artificial Neural Networks and Machine Learning – ICANN 2020, 633–46. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-61609-0_50.
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Kazi, Anees, Shadi Albarqouni, Amelia Jimenez Sanchez, Sonja Kirchhoff, Peter Biberthaler, Nassir Navab und Diana Mateus. „Automatic Classification of Proximal Femur Fractures Based on Attention Models“. In Machine Learning in Medical Imaging, 70–78. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67389-9_9.
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Li, Caizi, Qianqian Tong, Xiangyun Liao, Weixin Si, Yinzi Sun, Qiong Wang und Pheng-Ann Heng. „Attention Based Hierarchical Aggregation Network for 3D Left Atrial Segmentation“. In Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges, 255–64. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-12029-0_28.
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Zhou, Yuncheng, Ke Zhang, Xinzhe Luo, Sihan Wang und Xiahai Zhuang. „Anatomy Prior Based U-net for Pathology Segmentation with Attention“. In Statistical Atlases and Computational Models of the Heart. M&Ms and EMIDEC Challenges, 392–99. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-68107-4_41.
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Knoop, Dennis, Bertram Wortelen und Marcus Behrendt. „Semi-automatic Aggregation of Multiple Models of Visual Attention for Model-Based User Interface Evaluation“. In Engineering Psychology and Cognitive Ergonomics, 187–99. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-22507-0_15.
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Vaca-Recalde, Myriam E., Joshué Pérez und Javier Echanobe. „Driver Monitoring System Based on CNN Models: An Approach for Attention Level Detection“. In Lecture Notes in Computer Science, 575–83. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-62365-4_56.
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Bai, Ching-Yuan, Buo-Fu Chen und Hsuan-Tien Lin. „Benchmarking Tropical Cyclone Rapid Intensification with Satellite Images and Attention-Based Deep Models“. In Machine Learning and Knowledge Discovery in Databases: Applied Data Science Track, 497–512. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-67667-4_30.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "Attention based models"
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Ji Wan Han, P. C. R. Lane, N. Davey und Yi Sun. „Attention mechanisms and component-based face detection“. In 2009 International Conference on Methods and Models in Computer Science (ICM2CS). IEEE, 2009. http://dx.doi.org/10.1109/icm2cs.2009.5397992.
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Fornaciari, Tommaso, und Dirk Hovy. „Geolocation with Attention-Based Multitask Learning Models“. In Proceedings of the 5th Workshop on Noisy User-generated Text (W-NUT 2019). Stroudsburg, PA, USA: Association for Computational Linguistics, 2019. http://dx.doi.org/10.18653/v1/d19-5528.
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Haque, Albert, Alexandre Alahi und Li Fei-Fei. „Recurrent Attention Models for Depth-Based Person Identification“. In 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2016. http://dx.doi.org/10.1109/cvpr.2016.138.
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Rezaur rahman Chowdhury, F. A., Quan Wang, Ignacio Lopez Moreno und Li Wan. „Attention-Based Models for Text-Dependent Speaker Verification“. In ICASSP 2018 - 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2018. http://dx.doi.org/10.1109/icassp.2018.8461587.
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Zapotoczny, Michał, Piotr Pietrzak, Adrian Łańcucki und Jan Chorowski. „Lattice Generation in Attention-Based Speech Recognition Models“. In Interspeech 2019. ISCA: ISCA, 2019. http://dx.doi.org/10.21437/interspeech.2019-2667.
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Tapu, R., und T. Zaharia. „Salient object detection based on spatiotemporal attention models“. In 2013 IEEE International Conference on Consumer Electronics (ICCE). IEEE, 2013. http://dx.doi.org/10.1109/icce.2013.6486786.
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Shafiq, Muhammad Amir, Zhiling Long, Haibin Di, Ghassan AI Regib und Mohammed Deriche. „Fault Detection Using Attention Models Based on Visual Saliency“. In ICASSP 2018 - 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2018. http://dx.doi.org/10.1109/icassp.2018.8461508.
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Awad, Dounia, Matei Mancas, Nicolas Riche, Vincent Courboulay und Arnaud Revel. „A CBIR-based evaluation framework for visual attention models“. In 2015 23rd European Signal Processing Conference (EUSIPCO). IEEE, 2015. http://dx.doi.org/10.1109/eusipco.2015.7362639.
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Yu, Xiang, Ngoc Thang Vu und Jonas Kuhn. „Learning the Dyck Language with Attention-based Seq2Seq Models“. In Proceedings of the 2019 ACL Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP. Stroudsburg, PA, USA: Association for Computational Linguistics, 2019. http://dx.doi.org/10.18653/v1/w19-4815.
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Arvanitis, Nikolaos, Constantinos Constantinopoulos und Dimitrios Kosmopoulos. „Translation of Sign Language Glosses to Text Using Sequence-to-Sequence Attention Models“. In 2019 15th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS). IEEE, 2019. http://dx.doi.org/10.1109/sitis.2019.00056.
Der volle Inhalt der QuelleBerichte der Organisationen zum Thema "Attention based models"
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Yan, Yujie, und Jerome F. Hajjar. Automated Damage Assessment and Structural Modeling of Bridges with Visual Sensing Technology. Northeastern University, Mai 2021. http://dx.doi.org/10.17760/d20410114.
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Recent advances in visual sensing technology have gained much attention in the field of bridge inspection and management. Coupled with advanced robotic systems, state-of-the-art visual sensors can be used to obtain accurate documentation of bridges without the need for any special equipment or traffic closure. The captured visual sensor data can be post-processed to gather meaningful information for the bridge structures and hence to support bridge inspection and management. However, state-of-the-practice data postprocessing approaches require substantial manual operations, which can be time-consuming and expensive. The main objective of this study is to develop methods and algorithms to automate the post-processing of the visual sensor data towards the extraction of three main categories of information: 1) object information such as object identity, shapes, and spatial relationships - a novel heuristic-based method is proposed to automate the detection and recognition of main structural elements of steel girder bridges in both terrestrial and unmanned aerial vehicle (UAV)-based laser scanning data. Domain knowledge on the geometric and topological constraints of the structural elements is modeled and utilized as heuristics to guide the search as well as to reject erroneous detection results. 2) structural damage information, such as damage locations and quantities - to support the assessment of damage associated with small deformations, an advanced crack assessment method is proposed to enable automated detection and quantification of concrete cracks in critical structural elements based on UAV-based visual sensor data. In terms of damage associated with large deformations, based on the surface normal-based method proposed in Guldur et al. (2014), a new algorithm is developed to enhance the robustness of damage assessment for structural elements with curved surfaces. 3) three-dimensional volumetric models - the object information extracted from the laser scanning data is exploited to create a complete geometric representation for each structural element. In addition, mesh generation algorithms are developed to automatically convert the geometric representations into conformal all-hexahedron finite element meshes, which can be finally assembled to create a finite element model of the entire bridge. To validate the effectiveness of the developed methods and algorithms, several field data collections have been conducted to collect both the visual sensor data and the physical measurements from experimental specimens and in-service bridges. The data were collected using both terrestrial laser scanners combined with images, and laser scanners and cameras mounted to unmanned aerial vehicles.
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Rusk, Todd, Ryan Siegel, Linda Larsen, Tim Lindsey und Brian Deal. Technical and Financial Feasibility Study for Installation of Solar Panels at IDOT-owned Facilities. Illinois Center for Transportation, August 2021. http://dx.doi.org/10.36501/0197-9191/21-024.
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The Smart Energy Design Assistance Center assessed the administrative, technical, and economic aspects of feasibility related to the procurement and installation of photovoltaic solar systems on IDOT-owned buildings and lands. To address administrative feasibility, we explored three main ways in which IDOT could procure solar projects: power purchase agreement (PPA), direct purchase, and land lease development. Of the three methods, PPA and direct purchase are most applicable for IDOT. While solar development is not free of obstacles for IDOT, it is administratively feasible, and regulatory hurdles can be adequately met given suitable planning and implementation. To evaluate IDOT assets for solar feasibility, more than 1,000 IDOT sites were screened and narrowed using spatial analytic tools. A stakeholder feedback process was used to select five case study sites that allowed for a range of solar development types, from large utility-scale projects to small rooftop systems. To evaluate financial feasibility, discussions with developers and datapoints from the literature were used to create financial models. A large solar project request by IDOT can be expected to generate considerable attention from developers and potentially attractive PPA pricing that would generate immediate cash flow savings for IDOT. Procurement partnerships with other state agencies will create opportunities for even larger projects with better pricing. However, in the near term, it may be difficult for IDOT to identify small rooftop or other small on-site solar projects that are financially feasible. This project identified two especially promising solar sites so that IDOT can evaluate other solar site development opportunities in the future. This project also developed a web-based decision-support tool so IDOT can identify potential sites and develop preliminary indications of feasibility. We recommend that IDOT begin the process of developing at least one of their large sites to support solar electric power generation.
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Scoular, Claire, und Ian Teo. Developing strategic plans for an aligned approach to 21st century skills integration. Australian Council for Educational Research, März 2021. http://dx.doi.org/10.37517/978-1-74286-626-0.
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This report describes an online course developed to support education systems to build an aligned and sustainable approach to integration of 21st Century Skills (21CS). 21CS are those skills that are considered particularly important to succeed in today’s knowledge-based society in which innovation and technology are predominant. Prominent examples include critical thinking, creative thinking, and collaboration, and such skills need to be better understood in order for them to be integrated. While different countries may have their own frameworks or priorities surrounding 21CS, a consistent approach to integration can still be achieved with a shared understanding from all stakeholders within the system. The course objectives focused on supporting countries to develop a strategic plan for 21CS integration, providing resources to aid that plan, and building capacity to implement the plan. The specific learning objectives were to: Understand components and steps leading to 21CS alignment; Conduct a needs analysis, identifying which steps are currently being met, and which steps need more attention; Develop a strategic plan, identifying which steps are to be prioritized and in which order; Gain insights from other education systems from reflections on successful developments and lessons learned; and Engage in discussion within education systems and with other countries about the emerging area of skills integration, as well as identify future directions. Course participants joined from across 16 Asia Pacific countries and from the Education Quality and Assessment Programme for the Pacific Community (EQAP). The course comprised of eight modules that were spread over three weeks, with content hosted online through the Moodle platform.Each module consisted of pre-recorded video content (30-60 minutes) and team and/or individual activities. The modules were supported by three live sessions that allowed participants to ask questions and share reflections in real time. The course concluded with a webinar that consisted of presentations that were delivered by one member from each Core Strategy Team who shared their team’s strategic plan and reflections from this course.
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Nagahi, Morteza, Raed Jaradat, Mohammad Nagahisarchoghaei, Ghodsieh Ghanbari, Sujan Poudyal und Simon Goerger. Effect of individual differences in predicting engineering students' performance : a case of education for sustainable development. Engineer Research and Development Center (U.S.), Mai 2021. http://dx.doi.org/10.21079/11681/40700.
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The academic performance of engineering students continues to receive attention in the literature. Despite that, there is a lack of studies in the literature investigating the simultaneous relationship between students' systems thinking (ST) skills, Five-Factor Model (FFM) personality traits, proactive personality scale, academic, demographic, family background factors, and their potential impact on academic performance. Three established instruments, namely, ST skills instrument with seven dimensions, FFM traits with five dimensions, and proactive personality with one dimension, along with a demographic survey, have been administrated for data collection. A cross-sectional web-based study applying Qualtrics has been developed to gather data from engineering students. To demonstrate the prediction power of the ST skills, FFM traits, proactive personality, academic, demographics, and family background factors on the academic performance of engineering students, two unsupervised learning algorithms applied. The study results identify that these unsupervised algorithms succeeded to cluster engineering students' performance regarding primary skills and characteristics. In other words, the variables used in this study are able to predict the academic performance of engineering students. This study also has provided significant implications and contributions to engineering education and education sustainable development bodies of knowledge. First, the study presents a better perception of engineering students' academic performance. The aim is to assist educators, teachers, mentors, college authorities, and other involved parties to discover students' individual differences for a more efficient education and guidance environment. Second, by a closer examination at the level of systemic thinking and its connection with FFM traits, proactive personality, academic, and demographic characteristics, understanding engineering students' skillset would be assisted better in the domain of sustainable education.