Hong Zhang
Computer Vision and Pattern Recognition · with Huang · 2019
A researcher in the Science corpus: 2 papers; trusts 156 researchers and is trusted by 5 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 62 citations into it; #12,612 of 21,575 by trust here, #12,172 by citations
- Artificial Intelligence — 44 citations into it; #20,253 of 35,345 by trust here, #18,186 by citations
- Model Architectures — 22 citations into it
- Efficiency & Compression — 21 citations into it
- Optimization & Training — 9 citations into it; #1,715 of 2,601 by trust here, #1,624 by citations
- Representation & Self-Supervised Learning — 7 citations into it
Whom Hong Zhang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Geoffrey E. Hinton
- Kaiming He
- Gao Huang
- Yoshua Bengio
- Ilya Sutskever
- Karen Simonyan
- Yann LeCun
- Ross B. Girshick
- Diederik P. Kingma
Who trusts Hong Zhang overall
Papers from Hong Zhang's perspective
Ordered by how strongly the researchers Hong Zhang 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)
- ImageNet: A large-scale hierarchical image database
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- 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
- Implicit Semantic Data Augmentation for Deep Networks (2019) — 242 citations
- Improved Techniques for Training Adaptive Deep Networks (2019) — 155 citations