Yurong Chen
Computer Vision and Pattern Recognition · 2016–2019
A researcher in the Science corpus: 8 papers; trusts 898 researchers and is trusted by 448 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 216 citations into it; #2,034 of 21,575 by trust here, #1,521 by citations
- Artificial Intelligence — 117 citations into it; #2,844 of 35,345 by trust here, #2,944 by citations
- Efficiency & Compression — 62 citations into it; #114 of 1,264 by trust here, #326 by citations
- Model Architectures — 40 citations into it
- Aerospace Engineering — 26 citations into it
- Optimization & Training — 18 citations into it
- Computational Mechanics — 12 citations into it
- Media Technology — 11 citations into it
Whom Yurong Chen trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Ross B. Girshick
- Kaiming He
- Geoffrey E. Hinton
- Karen Simonyan
- Yann LeCun
- Yoshua Bengio
- David G. Lowe
- Ilya Sutskever
- Andrew Zisserman
Who trusts Yurong Chen overall
- Aojun Zhou
- Yang He
- Frederick Tung
- Karim Ahmed
- Shifeng Zhang
- Arun Mallya
- Xiongwei Wu
- Tao Kong
- Georgios Georgiadis
- Wujie Wen
Papers from Yurong Chen's perspective
Ordered by how strongly the researchers Yurong Chen trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- Incremental Network Quantization: Towards Lossless CNNs with Low-Precision Weights (2017) — 1,135 citations
- DSOD: Learning Deeply Supervised Object Detectors from Scratch (2017) — 628 citations
- Dynamic Network Surgery for Efficient DNNs (2016) — 1,158 citations
- HyperNet: Towards Accurate Region Proposal Generation and Joint Object Detection (2016) — 853 citations
- RON: Reverse Connection with Objectness Prior Networks for Object Detection (2017) — 419 citations
- Explicit Loss-Error-Aware Quantization for Low-Bit Deep Neural Networks (2018) — 93 citations
- Learning Two-View Correspondences and Geometry Using Order-Aware Network (2019) — 368 citations
- Network Decoupling: From Regular to Depthwise Separable Convolutions (2018) — 100 citations