Hanqiu Deng

Computer Vision and Pattern Recognition · 2022–2023

A researcher in the Science corpus: 2 papers; trusts 346 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 75 citations into it
• Artificial Intelligence — 73 citations into it; #24,396 of 35,345 by trust here, #29,412 by citations
• Representation & Self-Supervised Learning — 26 citations into it
• Evaluation & Benchmarks — 10 citations into it
• Computer Networks and Communications — 6 citations into it; #6,479 of 9,886 by trust here, #7,832 by citations
• Generative Models — 6 citations into it
• Model Architectures — 6 citations into it
• Media Technology — 5 citations into it

Whom Hanqiu Deng trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Kaiming He
4. Diederik P. Kingma
5. Yann LeCun
6. Paul Bergmann
7. Ilya Sutskever
8. Yoshua Bengio
9. Jimmy Ba
10. Individualized Treat

Who trusts Hanqiu Deng overall

1. Zhikang Liu
2. Yang Zou
3. Xuan Zhang
4. Zhiyuan You
5. Tran Dinh Tien
6. Yiming Zhou
7. Jongheon Jeong
8. Shiyu Li
9. Lei Cui
10. Anh Tuan Nguyen

Papers from Hanqiu Deng's perspective

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

Their papers

• Prompt, Generate, Then Cache: Cascade of Foundation Models Makes Strong Few-Shot Learners (2023) — 245 citations
• Anomaly Detection via Reverse Distillation from One-Class Embedding (2022) — 945 citations