Min-Hung Chen
Computer Vision and Pattern Recognition · with Al-Regib · 2019
A researcher in the Science corpus: 1 paper; trusts 128 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 42 citations into it; #16,739 of 21,575 by trust here, #17,258 by citations
- Artificial Intelligence — 41 citations into it; #27,323 of 35,345 by trust here, #26,682 by citations
- Representation & Self-Supervised Learning — 16 citations into it; #2,566 of 3,145 by trust here, #2,757 by citations
Whom Min-Hung Chen trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Kaiming He
- Alex Krizhevsky
- Yoshua Bengio
- Karen Simonyan
- Andrew Zisserman
- Mingsheng Long
- Yann LeCun
- Sergey Ioffe
- Ross B. Girshick
Who trusts Min-Hung Chen overall
Papers from Min-Hung Chen's perspective
Ordered by how strongly the researchers Min-Hung Chen trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- 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
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Temporal Attentive Alignment for Large-Scale Video Domain Adaptation (2019) — 209 citations