Changhe Tu

Computer Vision and Pattern Recognition · 2016–2020

A researcher in the Science corpus: 2 papers; trusts 140 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 68 citations into it
• Artificial Intelligence — 35 citations into it
• Model Architectures — 11 citations into it
• Representation & Self-Supervised Learning — 6 citations into it

Whom Changhe Tu trusts overall

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

1. Alex Krizhevsky
2. Kaiming He
3. Geoffrey E. Hinton
4. Ross B. Girshick
5. Ilya Sutskever
6. Shaoqing Ren

Papers from Changhe Tu's perspective

Ordered by how strongly the researchers Changhe Tu 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
4. Going deeper with convolutions
5. ImageNet Large Scale Visual Recognition Challenge
6. Learning Multiple Layers of Features from Tiny Images
7. Gradient-based learning applied to document recognition
8. ImageNet: A large-scale hierarchical image database
9. Microsoft COCO: Common Objects in Context
10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers

• Synthesizing Training Images for Boosting Human 3D Pose Estimation (2016) — 299 citations
• DO-Conv: Depthwise Over-Parameterized Convolutional Layer (2020) — 251 citations