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of 442
pro vyhledávání: '"Leung, Howard"'
Learning view-invariant representation is a key to improving feature discrimination power for skeleton-based action recognition. Existing approaches cannot effectively remove the impact of viewpoint due to the implicit view-dependent representations.
Externí odkaz:
http://arxiv.org/abs/2304.00858
Musculoskeletal and neurological disorders are the most common causes of walking problems among older people, and they often lead to diminished quality of life. Analyzing walking motion data manually requires trained professionals and the evaluations
Externí odkaz:
http://arxiv.org/abs/2208.08848
Creating realistic characters that can react to the users' or another character's movement can benefit computer graphics, games and virtual reality hugely. However, synthesizing such reactive motions in human-human interactions is a challenging task
Externí odkaz:
http://arxiv.org/abs/2110.00380
Autor:
Liu, Xiaoyu, Liu, Man, Wu, Haoran, Tang, Wenshu, Yang, Weiqin, Chan, Thomas T.H., Zhang, Lingyun, Chen, Shufen, Xiong, Zhewen, Liang, Jianxin, Wai-Yiu Si-Tou, Willis, Shu, Ting, Li, Jingqing, Cao, Jianquan, Zhong, Chengpeng, Sun, Hanyong, Kwong, Tsz Tung, Leung, Howard H.W., Wong, John, Bo-San Lai, Paul, To, Ka-Fai, Xiang, Tingxiu, Jao-Yiu Sung, Joseph, Chan, Stephen Lam, Zhou, Jingying, Sze-Lok Cheng, Alfred
Publikováno v:
In JHEP Reports July 2024 6(7)
Early prediction of cerebral palsy is essential as it leads to early treatment and monitoring. Deep learning has shown promising results in biomedical engineering thanks to its capacity of modelling complicated data with its non-linear architecture.
Externí odkaz:
http://arxiv.org/abs/2106.04471
Autor:
Chao, Xianjin, Bin, Yanrui, Chu, Wenqing, Cao, Xuan, Ge, Yanhao, Wang, Chengjie, Li, Jilin, Huang, Feiyue, Leung, Howard
Human motion prediction aims to predict future 3D skeletal sequences by giving a limited human motion as inputs. Two popular methods, recurrent neural networks and feed-forward deep networks, are able to predict rough motion trend, but motion details
Externí odkaz:
http://arxiv.org/abs/2011.11221
Combining skeleton structure with graph convolutional networks has achieved remarkable performance in human action recognition. Since current research focuses on designing basic graph for representing skeleton data, these embedding features contain b
Externí odkaz:
http://arxiv.org/abs/2003.03007
Autor:
Allende, Daniela S, Amaddeo, Giuliana, Argemi, Josepmaria, Baulande, Sylvain, Beaufrère, Aurélie, Bermúdez-Ramos, María, Boulagnon-Rombi, Camille, Boursier, Jérôme, Bruges, Léa, Calderaro, Julien, Campani, Claudia, Caruso, Stefano, Casadei-Gardini, Andrea, Castano Garcia, Andres, Chan, Stephen Lam, D'Alessio, Antonio, Di Tommaso, Luca, Diaz, Alba, Digklia, Antonia, Dufour, Jean-François, Garcia-Porrero, Guillermo, Ghaffari Laleh, Narmin, Gnemmi, Viviane, Gopal, Purva, Graham, Rondell P., Heurgué, Alexandra, Iavarone, Massimo, Iñarrairaegui, Mercedes, Kather, Jakob Nikolas, Klein, Christophe, Labgaa, Ismail, Lameiras, Sonia, Legoix, Patricia, Lequoy, Marie, Leung, Howard Ho-Wai, Loménie, Nicolas, Maggioni, Marco, Maille, Pascale, Marín-Zuluaga, Juan Ignacio, Mendoza-Pacas, Guillermo, Michalak, Sophie, Mínguez, Beatriz, El Nahhas, Omar S M, Nault, Jean-Charles, Navale, Pooja, Ningarhari, Massih, Paradis, Valérie, Park, Young Nyun, Pawlotsky, Jean-Michel, Pedica, Federica, Perbellini, Riccardo, Peter, Simon, Pinato, David James, Pinter, Matthias, Radu, Pompilia, Regnault, Hélène, Reig, Maria, Rela, Mohamed, Rhee, Hyungjin, Rimassa, Lorenza, Rimini, Margherita, Salcedo, María Teresa, Sangro, Bruno, Scheiner, Bernhard, Sempoux, Christine, Su, Tung-Hung, Torres, Callie, Tran, Nguyen H, Trépo, Eric, Varela, Maria, Verset, Gontran, Vij, Mukul, Vogel, Arndt, Wendum, Dominique, Zeng, Qinghe, Ziol, Marianne
Publikováno v:
In The Lancet Oncology December 2023 24(12):1411-1422