Meng Yang
Computer Vision and Pattern Recognition · Vision · 2010–2018
A researcher in the Science corpus: 8 papers; trusts 663 researchers and is trusted by 67 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 177 citations into it; #3,482 of 21,575 by trust here, #3,426 by citations
- Computational Mechanics — 66 citations into it; #1,817 of 10,001 by trust here, #1,711 by citations
- Artificial Intelligence — 40 citations into it; #13,270 of 35,345 by trust here, #8,210 by citations
- Signal Processing — 35 citations into it; #2,365 of 7,572 by trust here, #4,750 by citations
- Media Technology — 25 citations into it; #3,170 of 3,621 by trust here, #3,430 by citations
- Representation & Self-Supervised Learning — 18 citations into it
- Model Architectures — 16 citations into it; #974 of 2,278 by trust here, #789 by citations
- Optimization & Training — 12 citations into it; #1,271 of 2,601 by trust here, #759 by citations
Whom Meng Yang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Michael Elad
- Julien Mairal
- Barbara Olshausen
- John Wright
- Jian Yang
- Peter N. Belhumeur
- Stéphane Mallat
- Michal Aharon
- Geoffrey E. Hinton
- Alex Krizhevsky
Who trusts Meng Yang overall
- Lei Zhang
- Mehrtash Harandi
- Zheng Zhang
- Xiangchu Feng
- David Dapeng Zhang
- Os Keyes
- Jian Yang
- Ran He
- Shuhang Gu
- Cheng Chen
Papers from Meng Yang's perspective
Ordered by how strongly the researchers Meng Yang 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
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet Large Scale Visual Recognition Challenge
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Large-Margin Softmax Loss for Convolutional Neural Networks (2016) — 1,593 citations
- Fisher Discrimination Dictionary Learning for sparse representation (2011) — 1,004 citations
- Sparse representation or collaborative representation: Which helps face recognition? (2011) — 2,080 citations
- Toward Characteristic-Preserving Image-based Virtual Try-On Network (2018) — 492 citations
- Gabor Feature Based Sparse Representation for Face Recognition with Gabor Occlusion Dictionary (2010) — 481 citations
- Robust sparse coding for face recognition (2011) — 624 citations
- Metaface learning for sparse representation based face recognition (2010) — 347 citations
- Sparse Representation Based Fisher Discrimination Dictionary Learning for Image Classification (2014) — 488 citations