Bradley Green

Computer Vision and Pattern Recognition · 2019–2023

A researcher in the Science corpus: 7 papers; trusts 676 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 208 citations into it; #12,182 of 21,575 by trust here, #5,890 by citations
• Artificial Intelligence — 191 citations into it
• Model Architectures — 50 citations into it
• Representation & Self-Supervised Learning — 27 citations into it
• Optimization & Training — 20 citations into it
• Radiology, Nuclear Medicine and Imaging — 19 citations into it
• Efficiency & Compression — 15 citations into it
• Media Technology — 5 citations into it

Whom Bradley Green trusts overall

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

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

Who trusts Bradley Green overall

1. Jeya Maria Jose Valanarasu
2. Huiyu Wang
3. Liang-Chieh Chen

Papers from Bradley Green's perspective

Ordered by how strongly the researchers Bradley Green 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. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
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

• Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation (2020) — 826 citations
• Boosting Image-based Mutual Gaze Detection using Pseudo 3D Gaze (2020) — 21 citations
• Towards Expert-Level Medical Question Answering with Large Language Models (2023) — 799 citations
• Joint Representation Learning and Novel Category Discovery on Single- and Multi-modal Data (2021) — 80 citations
• Towards Generalist Biomedical AI (2023) — 549 citations
• Deep Transformer Models for Time Series Forecasting: The Influenza Prevalence Case (2020) — 573 citations
• Search to Distill: Pearls Are Everywhere but Not the Eyes (2019) — 73 citations