Guiying Li

Computer Vision and Pattern Recognition · with Tang · 2016–2019

A researcher in the Science corpus: 4 papers; trusts 428 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 67 citations into it
• Artificial Intelligence — 39 citations into it; #35,295 of 35,345 by trust here, #28,481 by citations
• Optimization & Training — 20 citations into it; #2,600 of 2,601 by trust here, #2,378 by citations
• Computational Mechanics — 13 citations into it
• Efficiency & Compression — 13 citations into it
• Model Architectures — 12 citations into it
• Evaluation & Benchmarks — 7 citations into it
• Aerospace Engineering — 6 citations into it

Whom Guiying Li trusts overall

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

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

Who trusts Guiying Li overall

1. Ting-Wu Chin
2. Marta Garnelo

Papers from Guiying Li's perspective

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

Their papers

• Stochastic Gradient Descent for Nonconvex Learning Without Bounded Gradient Assumptions (2019) — 144 citations
• Efficient DNN Neuron Pruning by Minimizing Layer-wise Nonlinear Reconstruction Error (2018) — 47 citations
• Relief R-CNN: Utilizing Convolutional Features for Fast Object Detection (2016) — 7 citations
• Relief Impression Image Detection : Unsupervised Extracting Objects Directly From Feature Arrangements of Deep CNN (2016)