Zhengming Ding

Computer Vision and Pattern Recognition · 2016–2021

A researcher in the Science corpus: 9 papers; trusts 890 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 199 citations into it; #11,761 of 21,575 by trust here, #8,502 by citations
• Artificial Intelligence — 190 citations into it; #25,192 of 35,345 by trust here, #12,580 by citations
• Representation & Self-Supervised Learning — 98 citations into it; #2,406 of 3,145 by trust here, #2,558 by citations
• Radiology, Nuclear Medicine and Imaging — 27 citations into it
• Computational Mechanics — 15 citations into it
• Cancer Research — 14 citations into it
• Optimization & Training — 14 citations into it
• Model Architectures — 13 citations into it

Whom Zhengming Ding trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Alex Krizhevsky
4. Yann LeCun
5. Kaiming He
6. Ilya Sutskever
7. Diederik P. Kingma
8. Mingsheng Long
9. Ross B. Girshick
10. Karen Simonyan

Who trusts Zhengming Ding overall

1. Ishaan Gulrajani
2. David Lopez-Paz
3. Haohan Wang
4. Hao Wang
5. Jie Wen
6. Toshihiko Matsuura
7. Hongfu Liu
8. Changqing Zhang
9. Hongbin Lin
10. Xiaoqiang Yan

Papers from Zhengming Ding's perspective

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

Their papers

• 3D Human Pose Estimation with Spatial and Temporal Transformers (2021) — 692 citations
• Leveraging the Invariant Side of Generative Zero-Shot Learning (2019) — 338 citations
• Deep Domain Generalization With Structured Low-Rank Constraint (2018) — 145 citations
• Where and How to Transfer: Knowledge Aggregation-Induced Transferability Perception for Unsupervised Domain Adaptation (2021) — 153 citations
• Maximum Density Divergence for Domain Adaptation (2020) — 340 citations
• HGNet: Hybrid Generative Network for Zero-Shot Domain Adaptation (2020) — 22 citations
• Deep Domain Adaptation (2018) — 13 citations
• Multi-View Clustering via Deep Matrix Factorization (2017) — 522 citations
• Spectral Bisection Tree Guided Deep Adaptive Exemplar Autoencoder for Unsupervised Domain Adaptation (2016) — 19 citations