Ping Liang

Computer Vision and Pattern Recognition · 2016–2017

A researcher in the Science corpus: 2 papers; trusts 24 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 46 citations into it; #17,188 of 21,575 by trust here, #13,542 by citations
• Artificial Intelligence — 18 citations into it
• Representation & Self-Supervised Learning — 9 citations into it

Whom Ping Liang trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Pascal Vincent
4. Alex Krizhevsky
5. Yann LeCun
6. Ross B. Girshick

Who trusts Ping Liang overall

1. Zengqiang Yan

Papers from Ping Liang's perspective

Ordered by how strongly the researchers Ping Liang trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. ImageNet: A large-scale hierarchical image database
3. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
4. Going deeper with convolutions
5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
6. Gradient-based learning applied to document recognition
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
9. Long Short-Term Memory
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• Convolutional neural networks based transfer learning for diabetic retinopathy fundus image classification (2017) — 158 citations
• A Cross-Modality Learning Approach for Vessel Segmentation in Retinal Images (2016) — 534 citations