Liang Hong

Computer Vision and Pattern Recognition · with Li · 2020

A researcher in the Science corpus: 1 paper; trusts 19 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 19 citations into it
• Artificial Intelligence — 10 citations into it

Whom Liang Hong trusts

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

1. Ali Farhadi (in Computer Vision and Pattern Recognition)
2. Joseph Redmon (in Computer Vision and Pattern Recognition)
3. Kaiming He (in Computer Vision and Pattern Recognition)
4. Shaoqing Ren (in Computer Vision and Pattern Recognition)
5. X. Zhang (in Computer Vision and Pattern Recognition)
6. Ross B. Girshick (in Computer Vision and Pattern Recognition)
7. Davide Maltoni (in Artificial Intelligence)
8. Vincenzo Lomonaco (in Artificial Intelligence)
9. Roger Ratcliff (in Cognitive Science & Psychology)
10. Andrew Zisserman (in Computer Vision and Pattern Recognition)

Papers from Liang Hong's perspective

Ordered by how strongly the researchers Liang Hong 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. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
3. Distilling the Knowledge in a Neural Network (arXiv.org)
4. ImageNet classification with deep convolutional neural networks
5. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
7. Going deeper with convolutions
8. ImageNet Large Scale Visual Recognition Challenge
9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• CLRS: Continual Learning Benchmark for Remote Sensing Image Scene Classification (2020) — 66 citations