Jiaxiang Wu
Computer Vision and Pattern Recognition · with Cheng · 2013–2019
A researcher in the Science corpus: 5 papers; trusts 345 researchers and is trusted by 19 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 70 citations into it; #7,112 of 21,575 by trust here, #4,372 by citations
- Artificial Intelligence — 46 citations into it; #30,852 of 35,345 by trust here, #29,412 by citations
- Efficiency & Compression — 29 citations into it; #538 of 1,264 by trust here, #357 by citations
- Media Technology — 9 citations into it
- Model Architectures — 9 citations into it
- Information Retrieval & Search — 8 citations into it
- Computational Mechanics — 7 citations into it
- Computational Theory and Mathematics — 7 citations into it
Whom Jiaxiang Wu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Alex Krizhevsky
- Geoffrey E. Hinton
- Yann LeCun
- X. Zhang
- Karen Simonyan
- Yoshua Bengio
- Ross B. Girshick
- Andrew Zisserman
- Ilya Sutskever
Who trusts Jiaxiang Wu overall
- Haichuan Yang
- Georgios Georgiadis
- Felix Stahlberg
- Sehoon Kim
- Hongsong Wang
- Di Wu
- Jian-Hao Luo
- Yong Du
- Liang Wang
- Jindong Gu
Papers from Jiaxiang Wu's perspective
Ordered by how strongly the researchers Jiaxiang Wu trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Quantized Convolutional Neural Networks for Mobile Devices (2015) — 1,245 citations
- Fusing multi-modal features for gesture recognition (2013) — 72 citations
- Few Shot Network Compression via Cross Distillation (2019) — 69 citations
- Hashing for Distributed Data (2015) — 31 citations
- Online sketching hashing (2015) — 126 citations