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Статті в журналах з теми "Multi-view architectures"

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Tehrani, Mehrdad Panahpour, Michael Droese, Toshiaki Fujii, and Masayuki Tanimoto. "Distributed Source Coding Architectures for Multi-view Images." Journal of the Institute of Image Information and Television Engineers 58, no. 10 (2004): 1461–64. http://dx.doi.org/10.3169/itej.58.1461.

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Wang, Liang Hao, Ming Xi, Dong Xiao Li, and Ming Zhang. "A Network-Friendly Architecture for Multi-View Video Coding (MVC)." Advanced Materials Research 121-122 (June 2010): 678–81. http://dx.doi.org/10.4028/www.scientific.net/amr.121-122.678.

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Multi-view Video Coding (MVC) is very promising in applicable field for its 3D effect and interactive functions (multi viewpoint). In this paper, a network-friendly architecture for MVC is proposed. To exploit temporal as well as inter-view dependencies between adjacent cameras, two main features of the coder are used: hierarchical B picture and FGS (fine granularity scalable). Coding results are shown for the proposed multi-view coder and compared to the traditional coding architectures to show that our presented coding scheme outperforms the other approaches for the tested sequence.
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Koutris, Aristotelis, Theodoros Siozos, Yannis Kopsinis, Aggelos Pikrakis, Timon Merk, Matthias Mahlig, Stylianos Papaharalabos, and Peter Karlsson. "Deep Learning-Based Indoor Localization Using Multi-View BLE Signal." Sensors 22, no. 7 (April 2, 2022): 2759. http://dx.doi.org/10.3390/s22072759.

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In this paper, we present a novel Deep Neural Network-based indoor localization method that estimates the position of a Bluetooth Low Energy (BLE) transmitter (tag) by using the received signals’ characteristics at multiple Anchor Points (APs). We use the received signal strength indicator (RSSI) value and the in-phase and quadrature-phase (IQ) components of the received BLE signals at a single time instance to simultaneously estimate the angle of arrival (AoA) at all APs. Through supervised learning on simulated data, various machine learning (ML) architectures are trained to perform AoA estimation using varying subsets of anchor points. In the final stage of the system, the estimated AoA values are fed to a positioning engine which uses the least squares (LS) algorithm to estimate the position of the tag. The proposed architectures are trained and rigorously tested on several simulated room scenarios and are shown to achieve a localization accuracy of 70 cm. Moreover, the proposed systems possess generalization capabilities by being robust to modifications in the room’s content or anchors’ configuration. Additionally, some of the proposed architectures have the ability to distribute the computational load over the APs.
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Goktug Gurler, C., Anil Aksay, Gozde Bozdagi Akar, and A. Murat Tekalp. "Architectures for multi-threaded MVC-compliant multi-view video decoding and benchmark tests." Signal Processing: Image Communication 25, no. 5 (June 2010): 325–34. http://dx.doi.org/10.1016/j.image.2010.01.002.

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Ahn, Jun Hyong, Heung Cheol Kim, Jong Kook Rhim, Jeong Jin Park, Dick Sigmund, Min Chan Park, Jae Hoon Jeong, and Jin Pyeong Jeon. "Multi-View Convolutional Neural Networks in Rupture Risk Assessment of Small, Unruptured Intracranial Aneurysms." Journal of Personalized Medicine 11, no. 4 (March 24, 2021): 239. http://dx.doi.org/10.3390/jpm11040239.

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Auto-detection of cerebral aneurysms via convolutional neural network (CNN) is being increasingly reported. However, few studies to date have accurately predicted the risk, but not the diagnosis itself. We developed a multi-view CNN for the prediction of rupture risk involving small unruptured intracranial aneurysms (UIAs) based on three-dimensional (3D) digital subtraction angiography (DSA). The performance of a multi-view CNN-ResNet50 in accurately predicting the rupture risk (high vs. non-high) of UIAs in the anterior circulation measuring less than 7 mm in size was compared with various CNN architectures (AlexNet and VGG16), with similar type but different layers (ResNet101 and ResNet152), and single image-based CNN (single-view ResNet50). The sensitivity, specificity, and overall accuracy of risk prediction were estimated and compared according to CNN architecture. The study included 364 UIAs in training and 93 in test datasets. A multi-view CNN-ResNet50 exhibited a sensitivity of 81.82 (66.76–91.29)%, a specificity of 81.63 (67.50–90.76)%, and an overall accuracy of 81.72 (66.98–90.92)% for risk prediction. AlexNet, VGG16, ResNet101, ResNet152, and single-view CNN-ResNet50 showed similar specificity. However, the sensitivity and overall accuracy were decreased (AlexNet, 63.64% and 76.34%; VGG16, 68.18% and 74.19%; ResNet101, 68.18% and 73.12%; ResNet152, 54.55% and 72.04%; and single-view CNN-ResNet50, 50.00% and 64.52%) compared with multi-view CNN-ResNet50. Regarding F1 score, it was the highest in multi-view CNN-ResNet50 (80.90 (67.29–91.81)%). Our study suggests that multi-view CNN-ResNet50 may be feasible to assess the rupture risk in small-sized UIAs.
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Zhao, Haimei, Qiming Zhang, Shanshan Zhao, Zhe Chen, Jing Zhang, and Dacheng Tao. "SimDistill: Simulated Multi-Modal Distillation for BEV 3D Object Detection." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 7 (March 24, 2024): 7460–68. http://dx.doi.org/10.1609/aaai.v38i7.28577.

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Multi-view camera-based 3D object detection has become popular due to its low cost, but accurately inferring 3D geometry solely from camera data remains challenging and may lead to inferior performance. Although distilling precise 3D geometry knowledge from LiDAR data could help tackle this challenge, the benefits of LiDAR information could be greatly hindered by the significant modality gap between different sensory modalities. To address this issue, we propose a Simulated multi-modal Distillation (SimDistill) method by carefully crafting the model architecture and distillation strategy. Specifically, we devise multi-modal architectures for both teacher and student models, including a LiDAR-camera fusion-based teacher and a simulated fusion-based student. Owing to the ``identical'' architecture design, the student can mimic the teacher to generate multi-modal features with merely multi-view images as input, where a geometry compensation module is introduced to bridge the modality gap. Furthermore, we propose a comprehensive multi-modal distillation scheme that supports intra-modal, cross-modal, and multi-modal fusion distillation simultaneously in the Bird's-eye-view space. Incorporating them together, our SimDistill can learn better feature representations for 3D object detection while maintaining a cost-effective camera-only deployment. Extensive experiments validate the effectiveness and superiority of SimDistill over state-of-the-art methods, achieving an improvement of 4.8% mAP and 4.1% NDS over the baseline detector. The source code will be released at https://github.com/ViTAE-Transformer/SimDistill.
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Suwarningsih, Wiwin, Ana Heryana, Dianadewi Riswantini, Ekasari Nugraheni, and Dikdik Krisnandi. "The multi-tenancy queueing system “QuAntri” for public service mall." Bulletin of Electrical Engineering and Informatics 11, no. 5 (October 1, 2022): 2663–71. http://dx.doi.org/10.11591/eei.v11i5.4348.

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In the new-normal era, public services must make various adjustments to keep the community safe during the COVID-19 pandemic. The Public Service Mall is an initiative to put several public services offices in a centralized location. However, it will create a crowd of people who want access to public service. This paper evaluates multi-tenant models with the rapid adaptation of cloud computing technology for all organizations' shapes and sizes, focusing on multi-tenants and multi-services, where each tenant might have multiple services to offer. We also proposed a multi-tenant architecture that can serve queues in several places to prevent the spread of COVID-19 due to the crowd of people in public places. The design of multi-tenants and multi-services applications should consider various aspects such as security, database, data communication, and user interface. We designed and built the "QuAntri'' business logic to simplify the process for multi-services in each tenant. The developed system is expected to improve tenants' performance and reduce the crowd in the public service. We compared our agile method for system development with some of the previous multi-tenant architectures. Our experiments showed that our method overall is better than the referenced model-view-controller (MVC), model-view-presenter (MVP), and model-model-view-presenter (M-MVP).
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Debats, Oscar A., Geert J. S. Litjens, and Henkjan J. Huisman. "Lymph node detection in MR Lymphography: false positive reduction using multi-view convolutional neural networks." PeerJ 7 (November 22, 2019): e8052. http://dx.doi.org/10.7717/peerj.8052.

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Purpose To investigate whether multi-view convolutional neural networks can improve a fully automated lymph node detection system for pelvic MR Lymphography (MRL) images of patients with prostate cancer. Methods A fully automated computer-aided detection (CAD) system had been previously developed to detect lymph nodes in MRL studies. The CAD system was extended with three types of 2D multi-view convolutional neural networks (CNN) aiming to reduce false positives (FP). A 2D multi-view CNN is an efficient approximation of a 3D CNN, and three types were evaluated: a 1-view, 3-view, and 9-view 2D CNN. The three deep learning CNN architectures were trained and configured on retrospective data of 240 prostate cancer patients that received MRL images as the standard of care between January 2008 and April 2010. The MRL used ferumoxtran-10 as a contrast agent and comprised at least two imaging sequences: a 3D T1-weighted and a 3D T2*-weighted sequence. A total of 5089 lymph nodes were annotated by two expert readers, reading in consensus. A first experiment compared the performance with and without CNNs and a second experiment compared the individual contribution of the 1-view, 3-view, or 9-view architecture to the performance. The performances were visually compared using free-receiver operating characteristic (FROC) analysis and statistically compared using partial area under the FROC curve analysis. Training and analysis were performed using bootstrapped FROC and 5-fold cross-validation. Results Adding multi-view CNNs significantly (p < 0.01) reduced false positive detections. The 3-view and 9-view CNN outperformed (p < 0.01) the 1-view CNN, reducing FP from 20.6 to 7.8/image at 80% sensitivity. Conclusion Multi-view convolutional neural networks significantly reduce false positives in a lymph node detection system for MRL images, and three orthogonal views are sufficient. At the achieved level of performance, CAD for MRL may help speed up finding lymph nodes and assessing them for potential metastatic involvement.
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Fuentes Reyes, M., P. d’Angelo, and F. Fraundorfer. "AN EVALUATION OF STEREO AND MULTIVIEW ALGORITHMS FOR 3D RECONSTRUCTION WITH SYNTHETIC DATA." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-1/W2-2023 (December 13, 2023): 1021–28. http://dx.doi.org/10.5194/isprs-archives-xlviii-1-w2-2023-1021-2023.

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Abstract. The reconstruction of 3D scenes from images has usually been addressed with two different strategies, namely stereo and multiview. The former requires rectified images and generates a disparity map, while the latter relies on the camera parameters and directly retrieves a depth map. For both cases, deep learning architectures have shown an outstanding performance. However, due to the differences between input and output data, the two strategies are difficult to compare on a common scene. Moreover, for remote sensing applications multi-view data is hard to acquire and the ground truth is either sparse or affected by outliers. Hence, in this article we evaluate the performance of stereo and multi-view architectures trained on synthetic data resembling remote sensing images. The data has been and processed and organized to be compatible with both kind of neural networks. For a fair comparison, training and testing are done only with two views. We focus on the accuracy of the reconstruction, as well as the impact of the depth range and the baseline of the stereo array. Results are presented for deep learning architectures and non-learning algorithms.
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Zhang, Yueping, Ao-Jan Su, and Guofei Jiang. "Understanding data center network architectures in virtualized environments: A view from multi-tier applications." Computer Networks 55, no. 9 (June 2011): 2196–208. http://dx.doi.org/10.1016/j.comnet.2011.03.001.

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Дисертації з теми "Multi-view architectures"

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Hasan, Md Raqibul. "Multi-core Architectures for Feed-forward Neural Networks." University of Dayton / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1395140542.

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Panda, Amayika. "A Novel Configurable Benchmarking System for Multi-core Architectures." University of Cincinnati / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1300479983.

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Chen, Hua. "FPGA Based Multi-core Architectures for Deep Learning Networks." University of Dayton / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1449417091.

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Agarwal, Navneet. "Autοmated depressiοn level estimatiοn : a study οn discοurse structure, input representatiοn and clinical reliability". Electronic Thesis or Diss., Normandie, 2024. http://www.theses.fr/2024NORMC215.

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Compte tenu de l'impact sévère et généralisé de la dépression, des initiatives de recherche significatives ont été entreprises pour définir des systèmes d'évaluation automatisée de la dépression. La recherche présentée dans cette thèse tourne autour des questions suivantes qui restent relativement inexplorées malgré leur pertinence dans le domaine de l'évaluation automatisée de la dépression : (1) le rôle de la structure du discours dans l'analyse de la santé mentale, (2) la pertinence de la représentation de l'entrée pour les capacités prédictives des modèles de réseaux neuronaux, et (3) l'importance de l'expertise du domaine dans la détection automatisée de la dépression.La nature dyadique des entretiens patient-thérapeute garantit la présence d'une structure sous-jacente complexe dans le discours. Dans cette thèse, nous établissons d'abord l'importance des questions du thérapeute dans l'entrée du modèle de réseau neuronal, avant de montrer qu'une combinaison séquentielle des entrées du patient et du thérapeute est une stratégie sous-optimale. Par conséquent, des architectures à vues multiples sont proposées comme moyen d'incorporer la structure du discours dans le processus d'apprentissage des réseaux neuronaux. Les résultats expérimentaux obtenus avec deux encodages de texte différents montrent les avantages des architectures multi-vues proposées, validant la pertinence de la conservation de la structure du discours dans le processus d'apprentissage du modèle.Ayant établi la nécessité de conserver la structure du discours dans le processus d'apprentissage, nous explorons plus avant les représentations textuelles basées sur les graphes. Les recherches menées dans ce contexte mettent en évidence l'impact des représentations d'entrée non seulement pour définir les capacités d'apprentissage du modèle, mais aussi pour comprendre leur processus prédictif. Les graphiques de similitude de phrases et les graphiques de corrélation de mots-clés sont utilisés pour illustrer la capacité des représentations graphiques à fournir des perspectives variées sur la même entrée, en mettant en évidence des informations qui peuvent non seulement améliorer les performances prédictives des modèles, mais aussi être pertinentes pour les professionnels de la santé. Le concept de vues multiples est également incorporé dans les deux structures graphiques afin de mettre en évidence les différences de perspectives entre le patient et le thérapeute au cours d'un même entretien. En outre, il est démontré que la visualisation des structures graphiques proposées peut fournir des informations précieuses indiquant des changements subtils dans le comportement du patient et du thérapeute, faisant allusion à l'état mental du patient.Enfin, nous soulignons le manque d'implication des professionnels de la santé dans le contexte de la détection automatique de la dépression basée sur des entretiens cliniques. Dans le cadre de cette thèse, des annotations cliniques de l'ensemble de données DAIC-WOZ ont été réalisées afin de fournir une ressource pour mener des recherches interdisciplinaires dans ce domaine. Des expériences sont définies pour étudier l'intégration des annotations cliniques dans les modèles de réseaux neuronaux appliqués à la tâche de prédiction au niveau des symptômes dans le domaine de la détection automatique de la dépression. En outre, les modèles proposés sont analysés dans le contexte des annotations cliniques afin d'établir une analogie entre leur processus prédictif et leurs tendances psychologiques et ceux des professionnels de la santé, ce qui constitue une étape vers l'établissement de ces modèles en tant qu'outils cliniques fiables
Given the severe and widespread impact of depression, significant research initiatives have been undertaken to define systems for automated depression assessment. The research presented in this dissertation revolves around the following questions that remain relatively unexplored despite their relevance within automated depression assessment domain; (1) the role of discourse structure in mental health analysis, (2) the relevance of input representation towards the predictive abilities of neural network models, and (3) the importance of domain expertise in automated depression detection.The dyadic nature of patient-therapist interviews ensures the presence of a complex underlying structure within the discourse. Within this thesis, we first establish the importance of therapist questions within the neural network model's input, before showing that a sequential combination of patient and therapist input is a sub-optimal strategy. Consequently, Multi-view architectures are proposed as a means of incorporating the discourse structure within the learning process of neural networks. Experimental results with two different text encodings show the advantages of the proposed multi-view architectures, validating the relevance of retaining discourse structure within the model's training process.Having established the need to retain the discourse structure within the learning process, we further explore graph based text representations. The research conducted in this context highlights the impact of input representations not only in defining the learning abilities of the model, but also in understanding their predictive process. Sentence Similarity Graphs and Keyword Correlation Graphs are used to exemplify the ability of graphical representations to provide varying perspectives of the same input, highlighting information that can not only improve the predictive performance of the models but can also be relevant for medical professionals. Multi-view concept is also incorporated within the two graph structures to further highlight the difference in the perspectives of the patient and the therapist within the same interview. Furthermore, it is shown that visualization of the proposed graph structures can provide valuable insights indicative of subtle changes in patient and therapist's behavior, hinting towards the mental state of the patient.Finally, we highlight the lack of involvement of medical professionals within the context of automated depression detection based on clinical interviews. As part of this thesis, clinical annotations of the DAIC-WOZ dataset were performed to provide a resource for conducting interdisciplinary research in this field. Experiments are defined to study the integration of the clinical annotations within the neural network models applied to symptom-level prediction task within the automated depression detection domain. Furthermore, the proposed models are analyzed in the context of the clinical annotations to analogize their predictive process and psychological tendencies with those of medical professionals, a step towards establishing them as reliable clinical tools
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Mao, Jialin. "CHARACTERIZATION OF POLYMER ARCHITECTURES AND SEQUENCES BY MULTI-STAGE MASS SPECTROMETRY." University of Akron / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=akron1554913939030297.

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Kim, Hyung Joon. "Multi-standard radio transceiver architectures and radio frequency front-end design." Connect to this title online, 2005. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1110399471.

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Thesis (Ph. D.)--Ohio State University, 2005.
Title from first page of PDF file. Document formatted into pages; contains xv, 128 p.; also includes graphics (some col.). Includes bibliographical references (p. 125-128). Available online via OhioLINK's ETD Center
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Persson, Magnus. "A Formalized Approach to Multi-View Components for Embedded Systems : Applied to Tool Integration, Run-Time Adaptivity and Architecture Exploration." Doctoral thesis, KTH, Inbyggda styrsystem, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-122487.

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Development of embedded systems poses an increasing challenge fordevelopers largely due to increasing complexity. Several factors contribute tothe complexity challenge: • the number of extra-functional properties applying to embedded systems,such as resource usage, timing effects, safety. • the functionality of embedded systems, to a larger extent than for othersoftware, involves engineers from multiple different disciplines, such asmechanical, control, software, safety, systems and electrical engineers.Themulti-disciplinarity causes the development environments to consistof separate data, models and tools. Several engineering paradigms to handle this complexity increase havebeen suggested, including methodologies focused on architecture, models andcomponents. In systems engineering, a long-standing approach has been todescribe the system in several views, each according to a certain viewpoint.By doing so, a divide-and-conquer strategy is applied to system concerns.Unfortunately, it is hard to always find completely independent concerns:there is always some semantic overlap between the different views. Modelbaseddesign (MBD) deals with building sound abstractions that can representa system under design and be used for analysis. Component-based design(CBD) focuses on how to build reusable component models with well-definedcomposition models. In this thesis, a concept of formalized multi-viewed component models (MVCM) is proposed, which integrates the three above mentioned paradigms.Principles and guidelines for MV CMs are developed. One of the main challengesfor the proposition is to provide MV CMs that produce composabilityboth along component boundaries and viewpoint boundaries. To accomplishthis, the relations between viewpoints need to be explicitly taken into account.Further, the semantic relations between these viewpoints need to be explicitlymodeled in order to efficiently ensure that the views are kept consistent. Asa main contribution, this thesis presents the formalization of the conceptsneeded to build such component models. A proper formalization of multiviewedconcerns provides several opportunities. Given suitable tool support, itwill be feasible to automate architecture analysis and architecture exploration. The thesis includes a number of case studies that provide insight andfeedback to the problem formulation and validating the results. The casestudies include a resource-aware reconfigurable middleware, a design of anarchitecture exploration methodology, and a windshield wiper system.

QC 20130527

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Xu, Zichen. "Energy Modeling and Management for Data Services in Multi-Tier Mobile Cloud Architectures." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1468272637.

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Su, Tianyu. "An Architecture for 3D Multi-view video Transmission based on Dynamic Adaptive Streaming over HTTP (DASH)." Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/32505.

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Recent advancement in cameras and image processing technology has generated a paradigm shift from traditional 2D and 3D video to Multi-view Video (MVV) technology, while at the same time improving video quality and compression through standards such as High Efficiency video Coding (HEVC). In multi-view, cameras are placed in predetermined positions to capture the video from various views. Delivering such views with high quality over the Internet is a challenging prospect, as MVV traffic is several times larger than traditional video since it consists of multiple video sequences each captured from a different angle, requiring more bandwidth than single view video to transmit MVV. Also, the Internet is known to be prone to packet loss, delay, and bandwidth variation, which adversely affects MVV transmission. Another challenge is that end users’ devices have different capabilities in terms of computing power, display, and access link capacity, requiring MVV to be adapted to each user’s context. In this paper, we propose an HEVC Multi-View system using Dynamic Adaptive Streaming over HTTP (DASH) to overcome the above mentioned challenges. Our system uses an adaptive mechanism to adjust the video bitrate to the variations of bandwidth in best effort networks. We also propose a novel scalable way for the Multi-view video and Depth (MVD) content for 3D video in terms of the number of transmitted views. Our objective measurements show that our method of transmitting MVV content can maximize the perceptual quality of virtual views after the rendering and hence increase the user’s quality of experience.
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Simon, Loïc. "Procedural reconstruction of buildings : towards large scale automatic 3D modeling of urban environments." Phd thesis, Ecole Centrale Paris, 2011. http://tel.archives-ouvertes.fr/tel-00637638.

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This thesis is devoted to 2D and 3D modeling of urban environments using structured representations and grammars. Our approach introduces a semantic representation for buildings that encodes expected architectural constraints and is able to derive complex instances using fairly simple grammars. Furthermore, we propose two novel inference algorithms to parse images using such grammars. To this end, a steepest ascent hill climbing concept is considered to derive the grammar and the corresponding parameters from a single facade view. It combines the grammar constraints with the expected visual properties of the different architectural elements. Towards addressing more complex scenarios and incorporating 3D information, a second inference strategy based on evolutionary computational algorithms is adopted to optimize a two-component objective function introducing depth cues. The proposed framework was evaluated qualitatively and quantitatively on a benchmark of annotated facades, demonstrating robustness to challenging situations. Substantial improvement due to the strong grammatical context was shown in comparison to the performance of the same appearance models coupled with local priors. Therefore, our approach provides powerful techniques in response to increasing demand on large scale 3D modeling of real environments through compact, structured and semantic representations, while opening new perspectives for image understanding
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Книги з теми "Multi-view architectures"

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Achmadi, Amanda, Paul Walker, and Soon-Tzu Speechley, eds. Architectural Encounters in Asia Pacific. Bloomsbury Publishing Plc, 2024. http://dx.doi.org/10.5040/9781350421394.

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Architectural Encounters in Asia Pacificexplores the architecture of colonial trade and industry, revealing a complex network of transnational connections across the built heritage of the world’s most dispersed and culturally diverse region. A wide-ranging collection of case studies uncover these forgotten connections, drawing together stories of migratory architects, imperial commodities, and indentured labour. From Iran to Tasmania, Japan to Java, and Imperial China to the Pacific Islands, the chapters reveal how remnants of colonial trade and industry shed light on the many multi-faceted mobilities of the imperial age, and their enduring legacy in the postcolonial built environments of Australasia, the Pacific, Southeast Asia and beyond. The chapters also reveal deep strands of cultural influences and material imprints long neglected by national histories of architecture, and showcase new methodologies to analyse the interconnectivities and bordering practices which are shaping our experiences of the 21st century. With almost every chapter arising from new archival sources, this richly interdisciplinary volume brings together the work of architectural historians, geographers and heritage practitioners to provide a new understanding of the rich and contested history of this region. This book illuminates a new geography of architectural histories through explorations of intracolonial encounters and exchanges across Asia Pacific (1800s-1940s). It reveals a complex field of transnational connectivity manifest in the built environments across of the world’s most disperse and culturally diverse region. Buildings for industry, agriculture, and trade in Australia, the Pacific and South-East Asia share an important but forgotten history of encounter, exchange, and influence. Industrial heritage is also under-represented in World Heritage lists, with the Asia Pacific region poorly represented and global connections between industrial sites insufficiently understood. This book addresses these research gaps by examining unprecedented buildings for trade and industrial-scale resource extraction across Asia-Pacific’s multiple colonial entities and their successor nation-states. The various chapters collected in this book help uncover these forgotten connections, drawing together stories of migratory architects, imperial commodities, and indentured labour. They reveal how remnants of colonial trade and industry shed light on the many multi-faceted mobilities of the imperial age, and their enduring legacy in the postcolonial built environments of Australasia, the Pacific, Southeast Asia and beyond. They reveal the deep strands of cultural influence and material imprints long neglected by national histories of architecture. They also showcase new methodologies to analyse the dialectics of interconnectivity and bordering practice that are shaping our experiences of the 21st century. This richly interdisciplinary volume brings together the works of architectural historians, architects, and heritage practitioners to provide a holistic view of the rich and contested architectural and urban history of this region.
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Oruc, Firat, ed. Sites of Pluralism. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780190052713.001.0001.

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Scholars and policymakers, struggling to make sense of the ongoing chaos in the Middle East, have focused on the possible causes of the escalation in both inter-state and intra-state conflict. But the Arab Spring has shown the urgent need for new ways to frame difference, both practically and theoretically. For some, a fundamental incompatibility between different ethno-linguistic and religious communities lies at the root of these conflicts; these divisions are thought to impede any form of political resolution or social cohesion. But little work has been done to explore how these tensions manifest themselves in the communities of the Middle East. Sites of Pluralism fills this significant gap, going beyond a narrow focus on 'minorities' to examine the larger canvas of community politics in the Middle East. Through eight case studies from esteemed experts in law, education, history, architecture, anthropology and political science, this multi-disciplinary volume offers a critical view of the Middle East's diverse, pluralistic fabric: how it has evolved throughout history; how it influences current political, economic and social dynamics; and what possibilities it offers for the future.
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Частини книг з теми "Multi-view architectures"

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Yang, Shaokang, Jianwei Niu, Jiyan Wu, and Xuefeng Liu. "Automatic Medical Image Report Generation with Multi-view and Multi-modal Attention Mechanism." In Algorithms and Architectures for Parallel Processing, 687–99. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60248-2_48.

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Hossain, Emdad, and Girija Chetty. "Gait Based Human Identity Recognition from Multi-view Surveillance Videos." In Algorithms and Architectures for Parallel Processing, 319–28. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33065-0_34.

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Chen, Yuhang, Sheng Liang, and Songwen Pei. "Multi-view Neighbor-Enriched Contrastive Learning Framework for Bundle Recommendation." In Algorithms and Architectures for Parallel Processing, 411–22. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-0798-0_24.

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Op de beeck, Steven, Marko van Dooren, Bert Lagaisse, and Wouter Joosen. "Modularity and Variability of Distributed Software Architectures through Multi-view Refinement of AO-Connectors." In Lecture Notes in Computer Science, 109–47. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36964-3_4.

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Dasarathy, Belur V. "Information Fusion as Aid for Qualitative Enhancement of Intelligence Extraction in Multi-source Environments - A Panoramic View of Architectures, Algorithms and Applications." In Intelligent Distributed Computing VI, 7. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-32524-3_2.

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Li, Zhongxue, Haiming Zhong, and Xike Wang. "Mapping Multi-view Architecture Products to Multi-agent Software Architecture Style." In Artificial Intelligence and Computational Intelligence, 249–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16527-6_32.

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Walletzký, Leonard, Luca Carrubbo, Angeliki Maria Toli, Mouzhi Ge, and Františka Romanovská. "Multi-contextual View to Smart City Architecture." In Advances in Intelligent Systems and Computing, 306–12. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-51057-2_42.

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He, Jingwu, Linbo Wang, Wanqing Zhao, Yang Zhang, Xu Han, Chenghao Guo, and Yanwen Guo. "Multi-view Viewpoint Assessment for Architectural Photos." In Advances in Multimedia Information Processing – PCM 2018, 503–13. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00764-5_46.

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Bisson, Gilles, and Clément Grimal. "An Architecture to Efficiently Learn Co-Similarities from Multi-view Datasets." In Neural Information Processing, 184–93. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34475-6_23.

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Li, Zihan, Wei Ding, Inal Mashukov, Scott Crouter, and Ping Chen. "A Multi-view Feature Construction and Multi-Encoder-Decoder Transformer Architecture for Time Series Classification." In Advances in Knowledge Discovery and Data Mining, 239–50. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-2266-2_19.

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Тези доповідей конференцій з теми "Multi-view architectures"

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Wang, Pei, Jiaming Liu, and Hui Zhang. "Multi-Layered Edge Computing Architecture of Smart Information System for Cross-View People Tracking." In 2024 4th International Conference on Machine Learning and Intelligent Systems Engineering (MLISE), 455–60. IEEE, 2024. http://dx.doi.org/10.1109/mlise62164.2024.10674584.

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Kim, Hyun-Min. "Design of an Automatic Load Positioning System for Hoist Operations." In Vertical Flight Society 72nd Annual Forum & Technology Display, 1–17. The Vertical Flight Society, 2016. http://dx.doi.org/10.4050/f-0072-2016-11451.

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The operation of a helicopter with an externally slung load is highly demanding for the flight crew. Without having a direct view on the load, the pilot needs assistance by a crew member for load handling, e.g. load positioning. During Helicopter Hoist Operations (HHO), the hoist operator gives instructions to the pilot and stabilizes the load motion. An automatic load positioning system for HHO is designed with the aim to reduce the workload of the flight crew and to improve the load handling performance. The control system consists of a multi-loop architecture that is designed using multi-objective optimization. The system was designed to achieve best performance in load positioning for the entire cable length range of the rescue hoist. Load positioning performance is a function of the cable length; faster automatic load positioning can be achieved with shorter cable lengths. This paper describes the overall design process covering the tools, control law architecture, optimization, and the validation using DLR's simulator.
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Issarny, Valérie, Titos Saridakis, and Apostolos Zarras. "Multi-view description of software architectures." In the third international workshop. New York, New York, USA: ACM Press, 1998. http://dx.doi.org/10.1145/288408.288429.

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Cheng, Chih-Hong, Yassine Hamza, and Harald Ruess. "Automated Analysis of Multi-View Software Architectures." In 2017 24th Asia-Pacific Software Engineering Conference (APSEC). IEEE, 2017. http://dx.doi.org/10.1109/apsec.2017.93.

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Liu, Wei, Songhe Feng, and Hui Tian. "Graph-based Multi-view Partial Multi-label Learning." In 2022 IEEE 13th International Symposium on Parallel Architectures, Algorithms and Programming (PAAP). IEEE, 2022. http://dx.doi.org/10.1109/paap56126.2022.10010429.

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Pittou, Maria, and Stavros Tripakis. "Multi-view consistency for infinitary regular languages." In 2016 International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation (SAMOS). IEEE, 2016. http://dx.doi.org/10.1109/samos.2016.7818342.

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Wang, Lijuan, Jinping Xing, Ming Yin, and Xinxuan Huang. "Multi-view Spectral Clustering With Adaptive Local Neighbors." In 2021 12th International Symposium on Parallel Architectures, Algorithms and Programming (PAAP). IEEE, 2021. http://dx.doi.org/10.1109/paap54281.2021.9720444.

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Gurler, C. Goktug, Anil Aksay, Gozde Bozdagi Akar, and A. Murat Tekalp. "Multi-threaded architectures and benchmark tests for real-time multi-view video decoding." In 2009 IEEE International Conference on Multimedia and Expo (ICME). IEEE, 2009. http://dx.doi.org/10.1109/icme.2009.5202480.

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Yao, Shizeng, Yangyang Wang, Hadi AliAkbarpour, Guna Seetharaman, Raghuveer Rao, and Kannappan Palaniappan. "SMVNet: Deep Learning Architectures for Accurate and Robust Multi-View Stereopsis." In 2020 IEEE Applied Imagery Pattern Recognition Workshop (AIPR). IEEE, 2020. http://dx.doi.org/10.1109/aipr50011.2020.9425188.

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Hu, Ruiting, Zhibin Gu, and Songhe Feng. "Joint Original Space and Latent Space for Multi-view Spectral Clustering." In 2022 IEEE 13th International Symposium on Parallel Architectures, Algorithms and Programming (PAAP). IEEE, 2022. http://dx.doi.org/10.1109/paap56126.2022.10010419.

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Звіти організацій з теми "Multi-view architectures"

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Balali, Vahid. System-of-Systems Integration for Civil Infrastructures Resiliency Toward MultiHazard Events. Mineta Transportation Institute, August 2023. http://dx.doi.org/10.31979/mti.2023.2245.

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Civil infrastructure systems—facilities that supply principal services, such as electricity, water, transportation, etc., to a community—are the backbone of modern society. These systems are frequently subject to multi-hazard events, such as earthquakes. The poor resiliency of these infrastructures results in many human casualties and significant economic losses every year. An outline of a holistic view that considers how different civil infrastructure systems operate independently and how they interact and communicate with each other is required to have a resilient infrastructure system. More specifically a systems engineering approach is required to enable infrastructure to remain resilient in the case of extreme events, including natural disasters. To address these challenges, this research builds on the proposal that the infrastructure systems be equipped with state-of-the-art sensor networks that continuously record the condition and performance of the infrastructure. The sensor data from each infrastructure are then transferred to a data analysis system component that employs artificial intelligence techniques to constantly analyze the infrastructure’s resiliency and energy efficiency performance. This research models the resilient infrastructure problem as a System of Systems (SoS) comprised of the abovementioned components. It explores system integration and operability challenges and proposes solutions to meet the requirements of the SoS. An integration ontology, as well as a data-centric architecture, is developed to enable infrastructure resiliency toward multi-hazard events. The Federal Emergency Management Agency (FEMA), and infrastructure managers, such as Departments of Transportation (DOTs) and the Federal Highway Administration (FHWA), can learn from and integrate these solutions to make civil infrastructure systems more resilient for all.
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Atkinson, Dan, and Alex Hale, eds. From Source to Sea: ScARF Marine and Maritime Panel Report. Society of Antiquaries of Scotland, September 2012. http://dx.doi.org/10.9750/scarf.09.2012.126.

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The main recommendations of the panel report can be summarised under four headings: 1. From Source to Sea: River systems, from their source to the sea and beyond, should form the focus for research projects, allowing the integration of all archaeological work carried out along their course. Future research should take a holistic view of the marine and maritime historic environment, from inland lakes that feed freshwater river routes, to tidal estuaries and out to the open sea. This view of the landscape/seascape encompasses a very broad range of archaeology and enables connections to be made without the restrictions of geographical or political boundaries. Research strategies, programmes From Source to Sea: ScARF Marine and Maritime Panel Report iii and projects can adopt this approach at multiple levels; from national to site-specific, with the aim of remaining holistic and cross-cutting. 2. Submerged Landscapes: The rising research profile of submerged landscapes has recently been embodied into a European Cooperation in Science and Technology (COST) Action; Submerged Prehistoric Archaeology and Landscapes of the Continental Shelf (SPLASHCOS), with exciting proposals for future research. Future work needs to be integrated with wider initiatives such as this on an international scale. Recent projects have begun to demonstrate the research potential for submerged landscapes in and beyond Scotland, as well as the need to collaborate with industrial partners, in order that commercially-created datasets can be accessed and used. More data is required in order to fully model the changing coastline around Scotland and develop predictive models of site survival. Such work is crucial to understanding life in early prehistoric Scotland, and how the earliest communities responded to a changing environment. 3. Marine & Maritime Historic Landscapes: Scotland’s coastal and intertidal zones and maritime hinterland encompass in-shore islands, trans-continental shipping lanes, ports and harbours, and transport infrastructure to intertidal fish-traps, and define understanding and conceptualisation of the liminal zone between the land and the sea. Due to the pervasive nature of the Marine and Maritime historic landscape, a holistic approach should be taken that incorporates evidence from a variety of sources including commercial and research archaeology, local and national societies, off-shore and onshore commercial development; and including studies derived from, but not limited to history, ethnology, cultural studies, folklore and architecture and involving a wide range of recording techniques ranging from photography, laser imaging, and sonar survey through to more orthodox drawn survey and excavation. 4. Collaboration: As is implicit in all the above, multi-disciplinary, collaborative, and cross-sector approaches are essential in order to ensure the capacity to meet the research challenges of the marine and maritime historic environment. There is a need for collaboration across the heritage sector and beyond, into specific areas of industry, science and the arts. Methods of communication amongst the constituent research individuals, institutions and networks should be developed, and dissemination of research results promoted. The formation of research communities, especially virtual centres of excellence, should be encouraged in order to build capacity.
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