Brady Zhou

Computer Vision and Pattern Recognition · 2019–2022

A researcher in the Science corpus: 3 papers; trusts 268 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 46 citations into it; #9,364 of 21,575 by trust here, #16,787 by citations
• Artificial Intelligence — 29 citations into it
• Aerospace Engineering — 19 citations into it; #1,934 of 6,421 by trust here, #4,388 by citations
• Reinforcement Learning — 19 citations into it
• Automotive Engineering — 15 citations into it
• Control and Systems Engineering — 8 citations into it
• Evaluation & Benchmarks — 8 citations into it
• Model Architectures — 6 citations into it

Whom Brady Zhou trusts overall

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

1. Diederik P. Kingma
2. Kaiming He
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Ross B. Girshick
6. Yann LeCun
7. Sergey Ioffe
8. Thomas Roddick
9. Yoshua Bengio
10. Alexey Dosovitskiy

Who trusts Brady Zhou overall

1. Kashyap Chitta
2. Aditya Prakash
3. Yunpeng Zhang
4. Ardi Tampuu
5. Runsheng Xu
6. Bencheng Liao
7. Yu-Quan Wang
8. Shaoyu Chen
9. Zhijian Liu
10. Bo Jiang

Papers from Brady Zhou's perspective

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

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

Their papers

• Cross-view Transformers for real-time Map-view Semantic Segmentation (2022) — 388 citations
• Does computer vision matter for action? (2019) — 119 citations
• Learning by Cheating (2019) — 689 citations