Relevant bibliographies by topics / Joint encoding

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Joint encoding'

Author: Grafiati
Published: 30 November 2024

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Journal articles on the topic "Joint encoding"

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Chapman, Christian, and Daniel W. Bliss. "Upper Bound on the Joint Entropy of Correlated Sources Encoded by Good Lattices." Entropy 21, no. 10 (September 29, 2019): 957. http://dx.doi.org/10.3390/e21100957.

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Lattices provide useful structure for distributed coding of correlated sources. A common lattice encoder construction is to first round an observed sequence to a `fine’ lattice with dither, then produce the result’s modulo to a `coarse’ lattice as the encoding. However, such encodings may be jointly-dependent. A class of upper bounds is established on the conditional entropy-rates of such encodings when sources are correlated and Gaussian and the lattices involved are a from an asymptotically-well-behaved sequence. These upper bounds guarantee existence of a joint–compression stage which can increase encoder efficiency. The bounds exploit the property that the amount of possible values for one encoding collapses when conditioned on other sufficiently informative encodings. The bounds are applied to the scenario of communicating through a many-help-one network in the presence of strong correlated Gaussian interferers, and such a joint–compression stage is seen to compensate for some of the inefficiency in certain simple encoder designs.
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Elbayad, Maha, Laurent Besacier, and Jakob Verbeek. "Joint source–target encoding with pervasive attention." Machine Translation 35, no. 4 (December 2021): 637–59. http://dx.doi.org/10.1007/s10590-021-09289-7.

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Kondi, L. P., G. Melnikov, and A. K. Katsaggelos. "Joint Optimal Object Shape Estimation and Encoding." IEEE Transactions on Circuits and Systems for Video Technology 14, no. 4 (April 2004): 528–33. http://dx.doi.org/10.1109/tcsvt.2004.825569.

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Rong, Dang, and Feng Gang. "Coordinate-Corrected and Graph-Convolution-Based Hand Pose Estimation Method." Sensors 24, no. 22 (November 14, 2024): 7289. http://dx.doi.org/10.3390/s24227289.

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To address the problem of low accuracy in joint point estimation in hand pose estimation methods due to the self-similarity of fingers and easy self-obscuration of hand joints, a hand pose estimation method based on coordinate correction and graph convolution is proposed. First, the standard coordinate encoding is improved by generating an unbiased heat map, and the distribution-aware method is used for decoding coordinates to reduce the error in decoding the coordinate encoding of joints. Then, the complex dependency relationship between the joints and the relationship between pixels and joints of the hand are modeled by using graph convolution, and the feature information of the hand joints is enhanced by determining the relationship between the hand joints. Finally, the skeletal constraint loss function is used to impose constraints on the joints, and a natural and undistorted hand skeleton structure is generated. Training tests are conducted on the public gesture interaction dataset STB, and the experimental results show that the method in this paper can reduce errors in hand joint point detection and improve the estimation accuracy.
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Rayes, Ramsey K., Rachel N. Mazorow, Leigh A. Mrotek, and Robert A. Scheidt. "Utility and Usability of Two Forms of Supplemental Vibrotactile Kinesthetic Feedback for Enhancing Movement Accuracy and Efficiency in Goal-Directed Reaching." Sensors 23, no. 12 (June 9, 2023): 5455. http://dx.doi.org/10.3390/s23125455.

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Recent advances in wearable sensors and computing have made possible the development of novel sensory augmentation technologies that promise to enhance human motor performance and quality of life in a wide range of applications. We compared the objective utility and subjective user experience for two biologically inspired ways to encode movement-related information into supplemental feedback for the real-time control of goal-directed reaching in healthy, neurologically intact adults. One encoding scheme mimicked visual feedback encoding by converting real-time hand position in a Cartesian frame of reference into supplemental kinesthetic feedback provided by a vibrotactile display attached to the non-moving arm and hand. The other approach mimicked proprioceptive encoding by providing real-time arm joint angle information via the vibrotactile display. We found that both encoding schemes had objective utility in that after a brief training period, both forms of supplemental feedback promoted improved reach accuracy in the absence of concurrent visual feedback over performance levels achieved using proprioception alone. Cartesian encoding promoted greater reductions in target capture errors in the absence of visual feedback (Cartesian: 59% improvement; Joint Angle: 21% improvement). Accuracy gains promoted by both encoding schemes came at a cost in terms of temporal efficiency; target capture times were considerably longer (1.5 s longer) when reaching with supplemental kinesthetic feedback than without. Furthermore, neither encoding scheme yielded movements that were particularly smooth, although movements made with joint angle encoding were smoother than movements with Cartesian encoding. Participant responses on user experience surveys indicate that both encoding schemes were motivating and that both yielded passable user satisfaction scores. However, only Cartesian endpoint encoding was found to have passable usability; participants felt more competent using Cartesian encoding than joint angle encoding. These results are expected to inform future efforts to develop wearable technology to enhance the accuracy and efficiency of goal-directed actions using continuous supplemental kinesthetic feedback.
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Dou Shuaifeng, 窦帅风, 雷鸣 Lei Ming, 沈学举 Shen Xueju, and 林超 Lin Chao. "Joint Fresnel Transform Correlator Based on Phase Encoding." Laser & Optoelectronics Progress 53, no. 12 (2016): 120701. http://dx.doi.org/10.3788/lop53.120701.

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Liu, Chen, Feng Li, Xian Sun, and Hongzhe Han. "Attention-Based Joint Entity Linking with Entity Embedding." Information 10, no. 2 (February 1, 2019): 46. http://dx.doi.org/10.3390/info10020046.

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Entity linking (also called entity disambiguation) aims to map the mentions in a given document to their corresponding entities in a target knowledge base. In order to build a high-quality entity linking system, efforts are made in three parts: Encoding of the entity, encoding of the mention context, and modeling the coherence among mentions. For the encoding of entity, we use long short term memory (LSTM) and a convolutional neural network (CNN) to encode the entity context and entity description, respectively. Then, we design a function to combine all the different entity information aspects, in order to generate unified, dense entity embeddings. For the encoding of mention context, unlike standard attention mechanisms which can only capture important individual words, we introduce a novel, attention mechanism-based LSTM model, which can effectively capture the important text spans around a given mention with a conditional random field (CRF) layer. In addition, we take the coherence among mentions into consideration with a Forward-Backward Algorithm, which is less time-consuming than previous methods. Our experimental results show that our model obtains a competitive, or even better, performance than state-of-the-art models across different datasets.
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Zhu, Dan, Zhuyuan Wang, Shenfei Zong, Hui Chen, Peng Chen, and Yiping Cui. "Wavenumber–intensity joint SERS encoding using silver nanoparticles for tumor cell targeting." RSC Adv. 4, no. 105 (2014): 60936–42. http://dx.doi.org/10.1039/c4ra11522h.

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A new optical encoding approach, the wavenumber–intensity joint surface enhanced Raman scattering (SERS) spectral encoding method, was demonstrated by using silver nanoparticles with a core–shell structure.
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Shin, Jaehun, Wonkee Lee, Byung-Hyun Go, Baikjin Jung, Youngkil Kim, and Jong-Hyeok Lee. "Exploration of Effective Attention Strategies for Neural Automatic Post-editing with Transformer." ACM Transactions on Asian and Low-Resource Language Information Processing 20, no. 6 (November 30, 2021): 1–17. http://dx.doi.org/10.1145/3465383.

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Automatic post-editing (APE) is the study of correcting translation errors in the output of an unknown machine translation (MT) system and has been considered as a method of improving translation quality without any modification to conventional MT systems. Recently, several variants of Transformer that take both the MT output and its corresponding source sentence as inputs have been proposed for APE; and models introducing an additional attention layer into the encoder to jointly encode the MT output with its source sentence recorded a high-rank in the WMT19 APE shared task. We examine the effectiveness of such joint-encoding strategy in a controlled environment and compare four types of decoder multi-source attention strategies that have been introduced into previous APE models. The experimental results indicate that the joint-encoding strategy is effective and that taking the final encoded representation of the source sentence is the more proper strategy than taking such representation within the same encoder stack. Furthermore, among the multi-source attention strategies combined with the joint-encoding, the strategy that applies attention to the concatenated input representation and the strategy that adds up the individual attention to each input improve the quality of APE results over the strategy using the joint-encoding only.
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Song, Wenjun, Congxian Li, and Qiuwen Zhang. "Rapid CU Partitioning and Joint Intra-Frame Mode Decision Algorithm." Electronics 13, no. 17 (August 31, 2024): 3465. http://dx.doi.org/10.3390/electronics13173465.

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H.266/Versatile Video Coding (VVC) introduces new techniques that build upon previous standards, proposing a nested multi-type tree quadtree (QTMT). The introduction of this structure significantly enhances video coding efficiency; additionally, the number of directional modes in H.266 has increased by 32 compared to H.265, accommodating a greater variety of texture patterns. However, the changes in the related structures have also led to a significant increase in encoding complexity. To address the issue of excessive computational complexity, this paper proposes a targeted rapid Coding Units segmenting approach combined with decision-making for an intra-frame modes algorithm. In the first phase of the algorithm, we extract different features for CU blocks of various sizes and input them into the decision tree model’s classifier for classification processing, determining the CU partitioning mode to prematurely terminate the partitioning, thereby reducing the encoding complexity to some extent. In the second phase of the algorithm, we put forward an intra-frame mode decision strategy grounded in gradient descent techniques with a bidirectional search mode. This maximizes the approach to the global optimum, thereby obtaining the optimal intra-frame mode and further reducing the encoding complexity. Experimentation has demonstrated that the algorithm achieves a 54.53% reduction in encoding time. In comparison, the BD-BR (Bitrate-Distortion Rate) only increases by 1.38%, striking an optimal balance between the fidelity of video and the efficacy of the encoding process.
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Dissertations / Theses on the topic "Joint encoding"

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Bulling, Duncan George Spencer. "Expression of the sensory neuropeptide encoding genes, βPPT-A and α-CGRP in adjuvant-induced joint inflammation." Thesis, University of Edinburgh, 1999. http://hdl.handle.net/1842/21663.

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Following the observation that individuals with hemiplegia or poliomyelitis resist the development of rheumatoid arthritis in the affected limb the sensory nervous system has been implicated in the aetiology of joint inflammation. Sensory neuropeptides, produced in dorsal root ganglia (DRG), released from central and peripheral terminals of sensory nerves upon noxious stimulation, are implicated in central and peripheral events underlying inflammation. Previous work has explored neuropeptide gene expression in DRG neurones in the Freund's Complete Adjuvant (FCA) model of unilateral tibio-tarsal joint inflammation. Within 8h of FCA injection, expression of mRNAs from the β preprotachykinin-A (β PPT-A) gene, encoding the sensory neuropeptides substance P and neurokinin A, and the α-calcitonin gene-related peptide (CGRP) encoding gene increase in small diameter innervating DRG neurones. Small diameter sensory nerves include the class of nerve implicated in the transmission of noxious stimuli. No changes occur in contralateral DRG neurones. A recent report of mRNAs encoding various transcription factors in innervating over the first 8h after FCA injection members showed that AP-2 mRNA increased in small diameter neurones within 1h of adjuvant injection, returning to control levels at subsequent time points. Despite members of the AP-1 transcription factor group been implicated in the control of PPT -A in vitro mRNAs encoding members of AP-1 family were not detected or showed no changes in expression. The same was found for NGF1-A and NGFI-B. The aim of this thesis was to utilise in-situ hybridisation to explore the early changes in βPPT-A and α-CGRP mRNAs, and the possible role of AP-2 in their regulation over the first 8h after FCA injection. Subsequent investigations were designed to investigate molecular mechanisms underlying changes in neuropeptide gene expression.
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Soto, Daniel. "Techniques to accelerate the transition to a new generation of terrestrial digital TV." Doctoral thesis, Universitat Pompeu Fabra, 2021. http://hdl.handle.net/10803/671364.

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This thesis explores the problem of compatibility between generations in the field of Digital Television, and proposes solutions to this problem. Since its inception, the DTV has been under development without taking into account the ability to continue receiving broadcasts with legacy equipment when a new generation is introduced. Therefore, when it comes time to introduce a new technology, a simulcast solution is usually used. The study carried out in this thesis explains the reasons why a traditional simulcast is a problem. As a concrete study example, the case of the transition from SD MPEG-2 to HD H.264 broadcasts according to the DVB-T standard is analyzed. And how this problem unnecessarily extends the transition periods between generations. In this way it postulates that one way to promote the development of new generations of Digital Television is precisely to shorten transition times. In order to facilitate the transition to a new generation, different technical solutions have been studied and developed that provide a certain degree of compatibility between generations. The results obtained conclude that it is not only feasible, but also desirable, to incorporate inter-generational compatibility solutions in Digital Television standards. Using the techniques described here, and others listed as future work, it would be possible for new standards and generations to incorporate this necessary capability.
Esta tesis explora el problema de la compatibilidad entre generaciones en el área de la Televisión Digital, y propone soluciones a ese problema. Desde su inicio, la TVD se ha ido desarrollando sin tener en cuenta la capacidad de seguir recibiendo emisiones con equipos antiguos cuando se introduce una nueva generación. Por lo tanto, cuando llega el momento de introducir una nueva tecnología, se suele utilizar una solución de emisión simultánea o simulcast. El estudio realizado en esta tesis explica las razones por las que un simulcast tradicional es un problema. Como ejemplo de estudio específico, se analiza el caso de la transición desde emisiones SD MPEG-2 a HD H.264 utilizando el estándar DVB-T. Y cómo esta dificultad alarga innecesariamente los períodos de transición entre generaciones. En esta línea se postula que una forma de promover la implantación de nuevas generaciones de Televisión Digital es precisamente acortando los tiempos de transición. Para facilitar la transición a una nueva generación, se han estudiado y desarrollado diferentes soluciones técnicas que proporcionan un cierto grado de compatibilidad entre generaciones. Los resultados obtenidos concluyen que no sólo es factible, sino también deseable, incorporar soluciones de compatibilidad intergeneracional en los estándares de Televisión Digital. Utilizando las técnicas aquí descritas, y otras enumeradas como trabajos futuros, sería posible que los nuevos estándares y generaciones incorporaren esta característica necesaria.
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Sadikine, Mohamed Amine. "Deep vascular segmentation with geometric and topological constraints." Electronic Thesis or Diss., Brest, 2024. http://www.theses.fr/2024BRES0042.

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Dans le domaine de l’analyse d’images médicales, la segmentation des vaisseaux sanguins joue un rôle clé dans l’amélioration du diagnostic assisté par ordinateur et de la planification chirurgicale. Ce travail introduit trois contributions innovantes en segmentation automatique de structures vasculaires. Premièrement, nous présentons une méthodologie qui améliore les architectures inspirées de U-Net avec un auto-encodeur convolutif semi-surcomplet qui intègre des a priori de forme pour améliorer la délimitation des vaisseaux, avec un focus particulier sur la caractérisation des structures fines. Ensuite, notre recherche se prolonge pour affiner la segmentation à travers un mécanisme d’encodage préalable conjoint qui fusionne des contraintes géométriques et topologiques, fournissant un espace latent unifié qui capture les informations contextuelles et la connectivité des vaisseaux et répondant ainsi aux défis posés par leur variabilité anatomique. Enfin, nous présentons une approche supervisée multi-tâches incorporant des tâches auxiliaires spécifiques à l’échelle et un apprentissage contrastif. Ces avancées représentent un pas en avant dans la segmentation vasculaire automatisée, offrant ainsi le potentiel d’améliorer les résultats cliniques dans une large gamme d’applications
In the evolving field of medical image analysis, blood vessel segmentation plays a key role in improving computer-aided diagnosis and surgical planning. This work combines three innovative contributions to advance the automatic segmentation of vascular structures. Firstly, we introduce a novel methodology that enhances U-Net inspired architectures with a semi-overcomplete convolutional auto-encoder that integrates shape priors to improve the delineation of intricate vascular systems, with a specific emphasis on characterizing fine structures. Subsequently, our research delves into enhancing vessel delineation through a novel joint prior encoding mechanism that combines geometric and topological constraints, providing a unified latent space that captures contextual information and connectivity of blood vessels, thereby addressing the challenges posed by their anatomical variability. Finally, we present a novel clustering technique for scale decomposition, along with a multi-task supervised approach that incorporates scale-specific auxiliary tasks and contrastive learning. These advances represent a step forward in reliable automated vascular segmentation, offering the potential to enhance clinical outcomes in a wide range of applications in clinical routine
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Chen, Yingwen. "XQuery Query Processing in Relational Systems." Thesis, University of Waterloo, 2004. http://hdl.handle.net/10012/1201.

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With the rapid growth of XML documents to serve as a popular and major media for storage and interchange of the data on the Web, there is an increasing interest in using existing traditional relational database techniques to store and/or query XML data. Since XQuery is becoming a standard XML query language, significant effort has been made in developing an efficient and comprehensive XQuery-to-SQL query processor. In this thesis, we design and implement an XQuery-to-SQL Query Processor based on the Dynamic Intervals approach. We also provide a comprehensive translation for XQuery basic operations and FLWR expressions. The query processor is able to translate a complex XQuery query, which might include arbitrarily composed and nested FLWR expressions, basic functions, and element constructors, into a single SQL query for RDBMS and a physical plan for the XQuery-enhanced Relational Engine. In order to produce efficient and concise SQL queries, succinct XQuery to SQL translation templates and the optimization algorithms for the SQL query generation are proposed and implemented. The preferable merge-join approach is also proposed to avoid the inefficient nested-loop evaluation for FLWR expressions. Merge-join patterns and query rewriting rules are designed to identify XQuery fragments that can utilize the efficient merge-join evaluation. Proofs of correctness of the approach are provided in the thesis. Experimental results justify the correctness of our work.
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施宣光. "Reversible Steganography for BTC-compressed Images Based on Information Encoding and Joint Neighboring Coding." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/69854057230916163759.

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碩士
國立彰化師範大學
資訊工程學系
102
Recently, reversible steganography becomes a popular research issue. More and more attention have been paid to reversible data hiding techniques for compressed images based on Vector Quantization(VQ),JPEG, and Block Truncation Coding(BTC),because it can recover both the host media and hidden data without distortion. Compared with other compressed method, BTC has a significantly low complexity and less memory requirement, it therefore becomes an ideal data hiding domain. Reversible information hiding is a technique that can restore the stego-media after extracting all the classified messages. Due to the high correlativity with adjacent pixels, a natural image usually contains several smooth regions. In this paper, we proposed a data hiding scheme to embed secret data in the compressed bit streams. Use the bitmap substituting and reconstructed levels replacing and information encoding to hide data in the compressed gray images. And finally we combine the joint neighboring coding technique to hide more information The experimental results show that the proposed method outperforms the previous methods in embedding capacity.
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Chiu, Chih-Ming, and 邱志明. "Joint Design of H.264 SVC/MGS Encoding, Extraction and Unequal Erasure Protection for Rateless Wireless Broadcasting." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/92124607963327045804.

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碩士
國立交通大學
資訊科學與工程研究所
100
This study aims to supple¬ment Scalable Video Coding (SVC) with the proper ex¬traction of SVC-NAL units and the corresponding UEP channel coding of extracted layers, so that the resultant bit¬-streams can exhibit near-optimal rate-distortion perfor¬mance in lossy broad-casting environments without the need of re-encoding the SVC bit¬streams. In this thesis, we propose a novel joint design system of SVC/MGS optimized rate-distortion extraction and Rateless UEP code to endow wireless SVC broadcasting. Through the analysis of SVC bit-streams, we obtained the design requirements of Rateless UEP code. And then we build a group of pictures (GOP) based rate-distortion optimized extraction model under a certain UEP code.
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Yu-Wei, Wang. "High order joint source channel decoding and conditional entropy encoding novel bridging techniques between performance and complexity /." 2004. http://etda.libraries.psu.edu/theses/approved/WorldWideIndex/ETD-444/index.html.

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Books on the topic "Joint encoding"

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Echterhoff, Gerald, and René Kopietz. The Socially Shared Nature of Memory: From Joint Encoding to Communication. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198737865.003.0007.

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This chapter explores incidental, indirect ways in which memory is shaped by interpersonal interaction and communication, that is, without collaboration of several individuals on an explicit memory task. The first section discusses research showing that encoding stimuli together with another person improves memory for the experience. Some studies examine memory effects from task sharing and joint action, while others explore effects of the mere joint experience of stimuli. The second section turns to effects of social sharing in communication on memory, specifically, the effects of conversational retellings and the audience-tuning effect on memory. Regarding explanations for the audience-tuning effect, the chapter focuses on shared reality theory and review evidence for the motives and goals underlying shared-reality creation.
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Mundy, Peter. A Neural Networks, Information-Processing Model of Joint Attention and Social-Cognitive Development. Edited by Philip David Zelazo. Oxford University Press, 2013. http://dx.doi.org/10.1093/oxfordhb/9780199958474.013.0010.

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A neural networks approach to the development of joint attention can inform the study of the nature of human social cognition, learning, and symbolic thought process. Joint attention development involves increments in the capacity to engage in simultaneous or parallel processing of information about one’s own attention and the attention of other people. Infant practice with joint attention is both a consequence and an organizer of a distributed and integrated brain network involving frontal and parietal cortical systems. In this chapter I discuss two hypotheses that stem from this model. One is that activation of this distributed network during coordinated attention enhances the depth of information processing and encoding beginning in the first year of life. I also propose that with development joint attention becomes internalized as the capacity to socially coordinate mental attention to internal representations. As this occurs the executive joint attention network makes vital contributions to the development of human social cognition and symbolic thinking.
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Book chapters on the topic "Joint encoding"

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Cai, Hua, Qing Xu, and Weilin Shen. "Complex Relative Position Encoding for Improving Joint Extraction of Entities and Relations." In Proceeding of 2021 International Conference on Wireless Communications, Networking and Applications, 644–55. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2456-9_66.

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AbstractRelative position encoding (RPE) is important for transformer based pretrained language model to capture sequence ordering of input tokens. Transformer based model can detect entity pairs along with their relation for joint extraction of entities and relations. However, prior works suffer from the redundant entity pairs, or ignore the important inner structure in the process of extracting entities and relations. To address these limitations, in this paper, we first use BERT with complex relative position encoding (cRPE) to encode the input text information, then decompose the joint extraction task into two interrelated subtasks, namely head entity extraction and tail entity relation extraction. Owing to the excellent feature representation and reasonable decomposition strategy, our model can fully capture the semantic interdependence between different steps, as well as reduce noise from irrelevant entity pairs. Experimental results show that the F1 score of our method outperforms previous baseline work, achieving a better result on NYT-multi dataset with F1 score of 0.935.
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Xie, Zhihua, and Zhengzi Wang. "Joint Encoding of Multi-scale LBP for Infrared Face Recognition." In Advances in Intelligent Systems and Computing, 269–76. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-12286-1_27.

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Zhang, Wei, Yuejing Zhang, and Aiyun Zhan. "Zero-Tree Wavelet Algorithm Joint with Huffman Encoding for Image Compression." In Lecture Notes in Computer Science, 176–85. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-49017-4_11.

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Ahlswede, R., and Z. Zhang. "Estimating with Randomized Encoding the Joint Empirical Distribution in a Correlated Source." In Lecture Notes in Computer Science, 535–46. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11889342_31.

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Saju, Gulfam, Alan Okinaka, and Yuchou Chang. "Exploiting Generative Adversarial Networks in Joint Sensitivity Encoding for Enhanced MRI Reconstruction." In Advances in Visual Computing, 443–51. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-47966-3_35.

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Zhang, Jiaxing, and Gunar Schirner. "Joint Algorithm Developing and System-Level Design: Case Study on Video Encoding." In IFIP Advances in Information and Communication Technology, 26–38. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38853-8_3.

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Giannakeris, Panagiotis, Georgios Meditskos, Konstantinos Avgerinakis, Stefanos Vrochidis, and Ioannis Kompatsiaris. "Real-Time Recognition of Daily Actions Based on 3D Joint Movements and Fisher Encoding." In MultiMedia Modeling, 601–13. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-37734-2_49.

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Rinderknecht, Christian. "Proving a Soundness Property for the Joint Design of ASN.1 and the Basic Encoding Rules." In System Analysis and Modeling, 154–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-31810-1_11.

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Lee, Chungcheng, and Chulung Chen. "Distortion Tolerant Color Pattern Recognition by Using Mach-Zehnder Joint Transform Correlator with Image Encoding Technique." In Lecture Notes in Electrical Engineering, 511–27. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-74938-9_35.

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Li, Lei, Xin Weng, Julia A. Schnabel, and Xiahai Zhuang. "Joint Left Atrial Segmentation and Scar Quantification Based on a DNN with Spatial Encoding and Shape Attention." In Medical Image Computing and Computer Assisted Intervention – MICCAI 2020, 118–27. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59719-1_12.

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Conference papers on the topic "Joint encoding"

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Sadikine, A., B. Badic, E. Ferrante, V. Noblet, P. Ballet, D. Visvikis, and P. H. Conze. "Deep Vessel Segmentation with Joint Multi-Prior Encoding." In 2024 IEEE International Symposium on Biomedical Imaging (ISBI), 1–5. IEEE, 2024. http://dx.doi.org/10.1109/isbi56570.2024.10635835.

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Zhong, Zhichao, Ling Luo, Xiaohan He, and Hao Li. "Temporal Encoding for Sequential Recommendation." In 2024 International Joint Conference on Neural Networks (IJCNN), 1–8. IEEE, 2024. http://dx.doi.org/10.1109/ijcnn60899.2024.10651120.

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Liang, Min-Yu, Yun-Chieh Chang, and Jason Lin. "Color Image Steganography with Authentication via Scalable Index Encoding." In 2024 19th Asia Joint Conference on Information Security (AsiaJCIS), 143–50. IEEE, 2024. http://dx.doi.org/10.1109/asiajcis64263.2024.00031.

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Chen, Si, and Bang Wang. "Encoding Individual Activation and Collective Diffusion Capability for Influence Maximization." In 2024 International Joint Conference on Neural Networks (IJCNN), 1–9. IEEE, 2024. http://dx.doi.org/10.1109/ijcnn60899.2024.10650712.

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Ye, Shujia, Ligang Cao, Chun Yuan, Hao Feng, Lihua Yang, Qianghua Li, Peng Sun, and Gang Li. "Stereo Matching Method with Integrated Geometric Encoding for Disparity Refinement." In 2024 International Joint Conference on Neural Networks (IJCNN), 1–10. IEEE, 2024. http://dx.doi.org/10.1109/ijcnn60899.2024.10650651.

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Ignatiev, Alexey, Antonio Morgado, and Joao Marques-Silva. "Cardinality Encodings for Graph Optimization Problems." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/91.

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Different optimization problems defined on graphs find application in complex network analysis. Existing propositional encodings render impractical the use of propositional satisfiability (SAT) and maximum satisfiability (MaxSAT) solvers for solving a variety of these problems on large graphs. This paper has two main contributions. First, the paper identifies sources of inefficiency in existing encodings for different optimization problems in graphs. Second, for the concrete case of the maximum clique problem, the paper develops a novel encoding which is shown to be far more compact than existing encodings for large sparse graphs. More importantly, the experimental results show that the proposed encoding enables existing SAT solvers to compute a maximum clique for large sparse networks, often more efficiently than the state of the art.
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Wang, Ruiwei, and Roland H. C. Yap. "Bipartite Encoding: A New Binary Encoding for Solving Non-Binary CSPs." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/165.

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Constraint Satisfaction Problems (CSPs) are typically solved with Generalized Arc Consistency (GAC). A general CSP can also be encoded into a binary CSP and solved with Arc Consistency (AC). The well-known Hidden Variable Encoding (HVE) is still a state-of-the-art binary encoding for solving CSPs. We propose a new binary encoding, called Bipartite Encoding (BE) which uses the idea of partitioning constraints. A BE encoded CSP can achieve a higher level of consistency than GAC on the original CSP. We give an algorithm for creating compact bipartite encoding for non-binary CSPs. We present a AC propagator on the binary constraints from BE exploiting their special structure. Experiments on a large set of non-binary CSP benchmarks with table constraints using the Wdeg, Activity and Impact heuristics show that BE with our AC propagator can outperform existing state-of-the-art GAC algorithms (CT, STRbit) and binary encodings (HVE with HTAC).
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Kunanbayev, Kassymzhomart, Islambek Temirbek, and Amin Zollanvari. "Complex Encoding." In 2021 International Joint Conference on Neural Networks (IJCNN). IEEE, 2021. http://dx.doi.org/10.1109/ijcnn52387.2021.9534094.

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Hsieh, Cheng-Han, and Jie-Hong R. Jiang. "Encoding Probabilistic Graphical Models into Stochastic Boolean Satisfiability." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/255.

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Statistical inference is a powerful technique in various applications. Although many statistical inference tools are available, answering inference queries involving complex quantification structures remains challenging. Recently, solvers for Stochastic Boolean Satisfiability (SSAT), a powerful formalism allowing concise encodings of PSPACE decision problems under uncertainty, are under active development and applied in more and more applications. In this work, we exploit SSAT solvers for the inference of Probabilistic Graphical Models (PGMs), an essential representation for probabilistic reasoning. Specifically, we develop encoding methods to systematically convert PGM inference problems into SSAT formulas for effective solving. Experimental results demonstrate that, by using our encoding, SSAT-based solving can complement existing PGM tools, especially in answering complex queries.
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Bofill, Miquel, Jordi Coll, Peter Nightingale, Josep Suy, Felix Ulrich-Oltean, and Mateu Villaret. "SAT Encodings for Pseudo-Boolean Constraints Together With At-Most-One Constraints (Extended Abstract)." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/769.

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When solving a combinatorial problem using propositional satisfiability (SAT), the encoding of the constraints is of vital importance. Pseudo-Boolean (PB) constraints appear frequently in a wide variety of problems. When PB constraints occur together with at-most-one (AMO) constraints over the same variables, they can be combined into PB(AMO) constraints. In this paper we present new encodings for PB(AMO) constraints. Our experiments show that these encodings can be substantially smaller than those of PB constraints and allow many more instances to be solved within a time limit. We also observed that there is no single overall winner among the considered encodings, but efficiency of each encoding may depend on PB(AMO) characteristics such as the magnitude of coefficient values.
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Reports on the topic "Joint encoding"

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Chalutz, Edo, Charles Wilson, Samir Droby, Victor Gaba, Clauzell Stevens, Robert Fluhr, and Y. Lu. Induction of Resistance to Postharvest Diseases and Extension of Shelf-Life of Fruits and Vegetables by Ultra-Violet Light. United States Department of Agriculture, February 1994. http://dx.doi.org/10.32747/1994.7568093.bard.

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Following preliminary observations by one of the collaborating scientists on this project and the completion of a 1-year, BARD-supported feasibility study (IS-1908-90F), this 3-year BARD project has been executed. The main objectives of the research were to elucidate biochemical and pathological aspects of UV-induced resistance in fruits and vegetables, to characterize physical and biological variables of induced resistance and delay of ripening, and to explore the application of the treatment as a control practice of postharvest diseases and shelf-life extension of fruits and vegetables. Our findings, which are detailed in numerous joint publications, have shown that the effect of UV-C light on induction of resistance and delay of ripening is a general one and of wide oddurrence. Apart from surface sterilization of the commodity, the reduction of decay of different fungi has been associated with and induced resistance phenomenon which gradually builds up within 24 to 48 hours after the UV treatment and can be reversed by visible light. In citrus, induced resistance has been associated with increased activity of the enzymes phenylalanine ammonia-lyase and peroxidase, and with the levels of endglucanase and chitinase. In tomato, resistance was correlated with the production of high levels of tomatine. Our study of some molecular aspects of the induced resistance in grapefruit has revealed the induction of a cDNA which represents a gene encoding for an isoflavone reductase-like protein that, in legumes, has been associated with phytoalexin biosynthesis. This gene was cloned and sequenced. Delay of ripening was associated in tomato with inhibition of ethylene production, carotenoid synthesis, and chlorophyll degradation and with the presence of high levels of polyamines. In peach fruit epiphytic populations of a yeast increased following the UV treatment. Pilot-size treatment and packing lines were constructed in the US and Israel to test the application of the UV treatment on a semi-commercial scale. Although effective in reduction of decay and delay of ripening, a number of problems will have to be addressed before practical application of this methodology can be realized. The main issues are associated with the temporal and variable response to the treatment, and its relationship to the maturity and date of harvest of the commodity.
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INVERSION METHOD OF UNCERTAIN PARAMETERS FOR TRUSS STRUCTURES BASED ON GRAPH NEURAL NETWORKS. The Hong Kong Institute of Steel Construction, December 2023. http://dx.doi.org/10.18057/ijasc.2023.19.4.5.

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Uncertainty exists widely in practical engineering. It is an important challenge in engineering structural analysis. In truss structures, the uncertainties of axial stiffness of bolted joints will significantly affect the mechanical behavior of the structure as the axial load is dominated by the member internal forces. Structural response analysis based on determined structural parameters is a common forward problem that can be solved by modeling analysis methods. However, the uncertainties parameter of axial stiffness of bolted joint cannot be determined during the design and analysis of truss structure in the direct nonlinear analysis method. Structural parameter identification based on structural response is a typical inverse problem in engineering, which is difficult to solve using traditional analysis tools. In this paper, an inverse model based on Graph Neural Network (GNN) is proposed. The feature encoding method for transforming truss structures into graph representations of GNN is defined. A parameterized acquisition method for large-scale datasets is presented, and an innovative inversion model based on GNN for the inversion of uncertain parameters of truss structures is proposed. The proposed method is shown to perform well with an inversion accuracy, and accurate results can be obtained with limited data sets. The inversion method has strong data mining capability and model interpretability, making it a promising direction for exploring engineering structural analysis.
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