Добірка наукової літератури з теми "Joint encoding"
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Статті в журналах з теми "Joint encoding"
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.
Повний текст джерелаElbayad, 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.
Повний текст джерелаKondi, 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.
Повний текст джерелаRong, 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.
Повний текст джерелаRayes, 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.
Повний текст джерелаDou 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.
Повний текст джерелаLiu, 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.
Повний текст джерелаZhu, 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.
Повний текст джерелаShin, 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.
Повний текст джерелаSong, 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.
Повний текст джерелаДисертації з теми "Joint encoding"
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.
Повний текст джерелаSoto, 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.
Повний текст джерелаEsta 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.
Sadikine, Mohamed Amine. "Deep vascular segmentation with geometric and topological constraints." Electronic Thesis or Diss., Brest, 2024. http://www.theses.fr/2024BRES0042.
Повний текст джерелаIn 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
Chen, Yingwen. "XQuery Query Processing in Relational Systems." Thesis, University of Waterloo, 2004. http://hdl.handle.net/10012/1201.
Повний текст джерела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.
Повний текст джерела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.
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.
Повний текст джерела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.
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.
Повний текст джерелаКниги з теми "Joint encoding"
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.
Повний текст джерелаMundy, 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.
Повний текст джерелаЧастини книг з теми "Joint encoding"
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.
Повний текст джерелаXie, 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.
Повний текст джерелаZhang, 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.
Повний текст джерелаAhlswede, 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.
Повний текст джерелаSaju, 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.
Повний текст джерелаZhang, 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.
Повний текст джерелаGiannakeris, 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.
Повний текст джерелаRinderknecht, 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.
Повний текст джерелаLee, 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.
Повний текст джерелаLi, 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.
Повний текст джерелаТези доповідей конференцій з теми "Joint encoding"
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.
Повний текст джерелаZhong, 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.
Повний текст джерелаLiang, 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.
Повний текст джерелаChen, 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.
Повний текст джерелаYe, 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.
Повний текст джерелаIgnatiev, 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.
Повний текст джерелаWang, 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.
Повний текст джерелаKunanbayev, 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.
Повний текст джерелаHsieh, 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.
Повний текст джерелаBofill, 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.
Повний текст джерелаЗвіти організацій з теми "Joint encoding"
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.
Повний текст джерелаINVERSION 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.
Повний текст джерела