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Статті в журналах з теми "Multi-view architectures"
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.
Повний текст джерелаWang, 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.
Повний текст джерелаKoutris, 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.
Повний текст джерелаGoktug 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.
Повний текст джерелаAhn, 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.
Повний текст джерелаZhao, 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.
Повний текст джерелаSuwarningsih, 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.
Повний текст джерелаDebats, 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.
Повний текст джерелаFuentes 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.
Повний текст джерелаZhang, 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.
Повний текст джерелаДисертації з теми "Multi-view architectures"
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.
Повний текст джерелаPanda, Amayika. "A Novel Configurable Benchmarking System for Multi-core Architectures." University of Cincinnati / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1300479983.
Повний текст джерелаChen, Hua. "FPGA Based Multi-core Architectures for Deep Learning Networks." University of Dayton / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1449417091.
Повний текст джерелаAgarwal, 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.
Повний текст джерелаGiven 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
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.
Повний текст джерелаKim, 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.
Повний текст джерелаTitle 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
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.
Повний текст джерелаQC 20130527
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.
Повний текст джерелаSu, 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.
Повний текст джерелаSimon, 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.
Повний текст джерелаКниги з теми "Multi-view architectures"
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.
Повний текст джерелаOruc, Firat, ed. Sites of Pluralism. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780190052713.001.0001.
Повний текст джерелаЧастини книг з теми "Multi-view architectures"
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.
Повний текст джерелаHossain, 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.
Повний текст джерелаChen, 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.
Повний текст джерелаOp 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.
Повний текст джерелаDasarathy, 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.
Повний текст джерелаLi, 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.
Повний текст джерелаWalletzký, 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.
Повний текст джерелаHe, 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.
Повний текст джерелаBisson, 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.
Повний текст джерелаLi, 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.
Повний текст джерелаТези доповідей конференцій з теми "Multi-view architectures"
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.
Повний текст джерелаKim, 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.
Повний текст джерелаIssarny, 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.
Повний текст джерелаCheng, 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.
Повний текст джерелаLiu, 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.
Повний текст джерелаPittou, 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.
Повний текст джерелаWang, 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.
Повний текст джерелаGurler, 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.
Повний текст джерелаYao, 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.
Повний текст джерелаHu, 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.
Повний текст джерелаЗвіти організацій з теми "Multi-view architectures"
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.
Повний текст джерелаAtkinson, 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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