Jinlong Hou

Computer Vision and Pattern Recognition · 2017–2019

A researcher in the Science corpus: 3 papers; trusts 136 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 35 citations into it
• Artificial Intelligence — 23 citations into it
• Evaluation & Benchmarks — 13 citations into it
• Representation & Self-Supervised Learning — 6 citations into it

Whom Jinlong Hou trusts overall

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

1. Alex Krizhevsky
2. Kaiming He
3. Geoffrey E. Hinton
4. Yann LeCun
5. Ross B. Girshick
6. Mark Everingham
7. Shaoqing Ren
8. Yoshua Bengio
9. Andrew Zisserman
10. Christian Szegedy

Papers from Jinlong Hou's perspective

Ordered by how strongly the researchers Jinlong Hou 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. Gradient-based learning applied to document recognition
4. ImageNet: A large-scale hierarchical image database
5. Going deeper with convolutions
6. Learning Multiple Layers of Features from Tiny Images
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Long Short-Term Memory
9. Attention is All you Need (Neural Information Processing Systems)
10. Microsoft COCO: Common Objects in Context

Their papers

• Tencent ML-Images: A Large-Scale Multi-Label Image Database for Visual Representation Learning (2019) — 95 citations
• CGBVS‐DNN: Prediction of Compound‐protein Interactions Based on Deep Learning (2017) — 64 citations
• From Whole Slide Imaging to Microscopy: Deep Microscopy Adaptation Network for Histopathology Cancer Image Classification (2019) — 70 citations