Ji Wan

Computer Vision and Pattern Recognition · with Li · 2014–2016

A researcher in the Science corpus: 2 papers; trusts 262 researchers and is trusted by 91 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 60 citations into it; #3,322 of 21,575 by trust here, #2,938 by citations
• Artificial Intelligence — 15 citations into it
• Aerospace Engineering — 10 citations into it; #644 of 6,421 by trust here, #470 by citations
• 3D Vision & Pose — 7 citations into it; #174 of 689 by trust here, #91 by citations
• Model Architectures — 5 citations into it

Whom Ji Wan trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Ross B. Girshick
4. Yann LeCun
5. Yoshua Bengio
6. Kaiming He
7. Ruslan Salakhutdinov
8. Ilya Sutskever
9. David G. Lowe
10. Karen Simonyan

Who trusts Ji Wan overall

1. Binh Yang
2. Shaoshuai Shi
3. Lei Tai
4. Kevin Qinghong Lin
5. Zhong-Qiu Zhao
6. Adnan Qayyum
7. Yanming Guo
8. Zetong Yang
9. Ming Liang
10. Yin Zhou

Papers from Ji Wan's perspective

Ordered by how strongly the researchers Ji Wan trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Multi-view 3D Object Detection Network for Autonomous Driving (2016) — 3,211 citations
• Deep Learning for Content-Based Image Retrieval: A Comprehensive Study (2014) — 938 citations