Fan Zhang

Computer Vision and Pattern Recognition · arXiv.org · 2015–2020

A researcher in the Science corpus: 11 papers; trusts 630 researchers and is trusted by 29 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 176 citations into it; #4,424 of 21,575 by trust here, #4,781 by citations
• Artificial Intelligence — 70 citations into it
• Media Technology — 41 citations into it; #377 of 3,621 by trust here, #500 by citations
• Computational Mechanics — 22 citations into it
• Model Architectures — 22 citations into it
• Representation & Self-Supervised Learning — 14 citations into it; #909 of 3,145 by trust here, #1,582 by citations
• Optimization & Training — 13 citations into it
• Remote Sensing — 8 citations into it

Whom Fan Zhang trusts overall

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

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

Who trusts Fan Zhang overall

1. Liangpei Zhang
2. Gong Cheng
3. Fan Hu
4. Gui-Song Xia
5. Souleyman Chaib
6. Yanfei Zhong
7. Jingwen Hu
8. Xiaoqiang Lu
9. Junwei Han
10. Ying Li

Papers from Fan Zhang's perspective

Ordered by how strongly the researchers Fan Zhang 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. 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. 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

• ACFNet: Attentional Class Feature Network for Semantic Segmentation (2019) — 301 citations
• A review on time series forecasting techniques for building energy consumption (2017) — 976 citations
• MediaPipe: A Framework for Building Perception Pipelines (2019) — 2,263 citations
• MediaPipe Hands: On-device Real-time Hand Tracking (2020) — 1,111 citations
• A full fuzzy-interval credibility-constrained nonlinear programming approach for irrigation water allocation under uncertainty (2020) — 49 citations
• BlazePose: On-device Real-time Body Pose tracking (2020) — 861 citations
• MediaPipe: A Framework for Perceiving and Processing Reality (2019) — 516 citations
• Brief review of image denoising techniques (2019) — 658 citations
• Weakly Supervised Learning Based on Coupled Convolutional Neural Networks for Aircraft Detection (2016) — 248 citations
• Scene Classification via a Gradient Boosting Random Convolutional Network Framework (2016) — 398 citations
• Saliency-Guided Unsupervised Feature Learning for Scene Classification (2015) — 528 citations