Jonathan Li

Computer Vision and Pattern Recognition · IEEE Transactions on Geoscience and Remote Sensing · 2010–2021

A researcher in the Science corpus: 5 papers; trusts 568 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 217 citations into it
• Artificial Intelligence — 92 citations into it
• Media Technology — 47 citations into it; #2,202 of 3,621 by trust here, #1,242 by citations
• Computational Mechanics — 44 citations into it
• Model Architectures — 35 citations into it
• Aerospace Engineering — 32 citations into it
• Environmental Engineering — 30 citations into it
• Atmospheric Science — 20 citations into it; #2,552 of 4,804 by trust here, #2,243 by citations

Whom Jonathan Li trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Ross B. Girshick
5. Karen Simonyan
6. Christian Szegedy
7. Sergey Ioffe
8. Ilya Sutskever
9. Yoshua Bengio
10. Yann LeCun

Who trusts Jonathan Li overall

1. Swalpa Kumar Roy
2. Mercedes Eugenia Paoletti
3. Guangrui Zhao
4. Xin He
5. Ava Vali
6. Qichao Liu
7. Alberto Signoroni
8. Wenju Wang
9. Juan Mario Haut
10. Rui Li

Papers from Jonathan Li's perspective

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

Their papers

• Squeeze-and-Attention Networks for Semantic Segmentation (2019) — 287 citations
• Spectral–Spatial Residual Network for Hyperspectral Image Classification: A 3-D Deep Learning Framework (2018) — 1,589 citations
• A Review on Deep Learning in UAV Remote Sensing (2021) — 471 citations
• Deep Learning for LiDAR Point Clouds in Autonomous Driving: A Review (2020) — 547 citations
• Oil spill detection from SAR intensity imagery using a marked point process (2010) — 47 citations