Liang Wang
Chinese Academy of Sciences
963 Papers
3.3K Citations
Liang Wang is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Computer science & Chemistry. The author has an hindex of 74, co-authored 645 publications. Previous affiliations of Liang Wang include Fudan University & University of Melbourne.
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Papers
Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding.
Roujian Lu,Xiang Zhao,Juan Li,Peihua Niu,Bo Yang,Honglong Wu,Wenling Wang,Hao Song,Baoying Huang,Na Zhu,Yuhai Bi,Xuejun Ma,Faxian Zhan,Liang Wang,Tao Hu,Hong Zhou,Zhenhong Hu,Weimin Zhou,Li Zhao,Jing Chen,Yao Meng,Ji Wang,Yang Lin,Jianying Yuan,Zhihao Xie,Jinmin Ma,William J. Liu,Dayan Wang,Wenbo Xu,Edward C. Holmes,George F. Gao,George F. Gao,Guizhen Wu,Weijun Chen,Weifeng Shi,Wenjie Tan,Wenjie Tan +36 more
TL;DR: The phylogenetic analysis suggests that bats might be the original host of this virus, an animal sold at the seafood market in Wuhan might represent an intermediate host facilitating the emergence of the virus in humans.
12.5K
A survey on visual surveillance of object motion and behaviors
Weiming Hu,Tieniu Tan,Liang Wang,Stephen J. Maybank +3 more
- 01 Aug 2004
TL;DR: This paper reviews recent developments and general strategies of the processing framework of visual surveillance in dynamic scenes, and analyzes possible research directions, e.g., occlusion handling, a combination of two and three-dimensional tracking, and fusion of information from multiple sensors, and remote surveillance.
Hierarchical recurrent neural network for skeleton based action recognition
Yong Du,Wei Wang,Liang Wang +2 more
- 07 Jun 2015
TL;DR: This paper proposes an end-to-end hierarchical RNN for skeleton based action recognition, and demonstrates that the model achieves the state-of-the-art performance with high computational efficiency.
Session-Based Recommendation with Graph Neural Networks
Shu Wu,Yuyuan Tang,Yanqiao Zhu,Liang Wang,Xing Xie,Tieniu Tan +5 more
- 17 Jul 2019
TL;DR: Wang et al. as discussed by the authors proposed Session-based Recommendation with Graph Neural Networks (SR-GNN) to capture complex transitions of items, which are difficult to be revealed by previous conventional sequential methods.
Silhouette analysis-based gait recognition for human identification
TL;DR: A simple but efficient gait recognition algorithm using spatial-temporal silhouette analysis is proposed that implicitly captures the structural and transitional characteristics of gait.
1.3K