Hao Jiang

Computer Vision and Pattern Recognition · 2 papers · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 32 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 106 citations into it
• Artificial Intelligence — 18 citations into it

Whom Hao Jiang trusts overall

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

1. Kaiming He
2. Joseph Redmon
3. Geoffrey E. Hinton
4. Ross B. Girshick
5. Alex Krizhevsky
6. Yann LeCun
7. Davide Maltoni
8. Vincenzo Lomonaco
9. Roger Ratcliff
10. Yoshua Bengio

Papers from Hao Jiang's perspective

Ordered by how strongly the researchers Hao Jiang 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. ImageNet: A large-scale hierarchical image database
4. Gradient-based learning applied to document recognition
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet Large Scale Visual Recognition Challenge
8. Going deeper with convolutions
9. Long Short-Term Memory
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Advancing Image Understanding in Poor Visibility Environments: A Collective Benchmark Study (2019) — 337 citations
• CLRS: Continual Learning Benchmark for Remote Sensing Image Scene Classification (2020) — 66 citations