Zengqiang Yan

Computer Vision and Pattern Recognition · 2018–2020

A researcher in the Science corpus: 3 papers; trusts 96 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 47 citations into it; #15,983 of 21,575 by trust here, #17,757 by citations
• Radiology, Nuclear Medicine and Imaging — 42 citations into it; #1,942 of 3,265 by trust here, #2,673 by citations
• Ophthalmology — 37 citations into it; #132 of 222 by trust here, #156 by citations
• Artificial Intelligence — 22 citations into it

Whom Zengqiang Yan trusts overall

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

1. Evan Shelhamer
2. Elisa Ricci
3. Alex Krizhevsky
4. Bashir Al-Diri
5. Carmen Alina Lupascu
6. José Ignacio Orlando
7. Geoffrey E. Hinton
8. Kaiming He
9. Trevor Darrell
10. Joes Staal

Who trusts Zengqiang Yan overall

1. Yao Zhou
2. Gary G. Yen
3. Zhang Yi

Papers from Zengqiang Yan's perspective

Ordered by how strongly the researchers Zengqiang Yan 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. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. ImageNet Large Scale Visual Recognition Challenge
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Enabling a Single Deep Learning Model for Accurate Gland Instance Segmentation: A Shape-Aware Adversarial Learning Framework (2020) — 44 citations
• A Three-Stage Deep Learning Model for Accurate Retinal Vessel Segmentation (2019) — 305 citations
• Joint Segment-Level and Pixel-Wise Losses for Deep Learning Based Retinal Vessel Segmentation (2018) — 385 citations