F
Feng Wu
Researcher at University of Science and Technology of China
Publications - 669
Citations - 19574
Feng Wu is an academic researcher from University of Science and Technology of China. The author has contributed to research in topics: Motion compensation & Data compression. The author has an hindex of 60, co-authored 645 publications receiving 15886 citations. Previous affiliations of Feng Wu include Center for Excellence in Education & Microsoft.
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Proceedings ArticleDOI
Design of a deployable underwater robot for the recovery of autonomous underwater vehicles based on origami technique
Jisen Li,Yang Yuliang,Yumei Zhang,Zhu Hua,Yongqi Li,Huang Qiujun,Lu Haibo,He Shan,Li Shengquan,Wei Zhang,Tao Mei,Feng Wu,Zhang Aidong +12 more
TL;DR: In this paper, a deployable underwater robot (DUR) for the recovery mission has been proposed, which can transform between open and closed states to maximize the performance at different recovery stages.
Proceedings ArticleDOI
Fractional compensation for spatial scalable video coding
Xiaoyan Sun,Feng Wu +1 more
TL;DR: A novel fractional compensation approach for spatial scalable video coding that simultaneously exploits inter layer correlation and intra layer correlation by learning-based mapping and does not need any motion bits.
Posted Content
Generalized Fault-Tolerance Topology Generation for Application Specific Network-on-Chips
TL;DR: Wang et al. as discussed by the authors proposed an integer linear programming (ILP) based method to generate ASNoC topologies, which can tolerate at most K faults in switches or links.
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Dynamic Attention guided Multi-Trajectory Analysis for Single Object Tracking
TL;DR: In this article, a dynamic appearance model that contains multiple target templates, each of which provides its own attention for locating the target in the new skyline frame, is proposed to improve tracking performance.
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End-to-End Image Compression with Probabilistic Decoding
TL;DR: In this article, a revertible neural network-based transform is used to convert pixels into coefficients that obey the pre-chosen distribution as much as possible, and the decoder may adopt different sampling strategies and produce diverse reconstructions, among which some have higher signal fidelity and some others have better visual quality.