Haojin Yang

Computer Vision and Pattern Recognition · 2012–2018

A researcher in the Science corpus: 4 papers; trusts 506 researchers and is trusted by 26 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 75 citations into it; #8,518 of 21,575 by trust here, #13,269 by citations
• Artificial Intelligence — 48 citations into it; #15,281 of 35,345 by trust here, #21,316 by citations
• Generative Models — 22 citations into it; #1,047 of 1,956 by trust here, #1,875 by citations
• Multimodal Learning — 18 citations into it
• Natural Language Processing — 16 citations into it
• Model Architectures — 12 citations into it
• Optimization & Training — 8 citations into it
• Statistical and Nonlinear Physics — 7 citations into it

Whom Haojin Yang trusts overall

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

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

Who trusts Haojin Yang overall

1. Max Jaderberg
2. Mingxia Liu
3. Andrea Vedaldi
4. Garrett Wilson
5. Jianfeng Dong
6. Divya Saxena
7. Meghavi Rana
8. Chintan Parmar
9. Zongwei Zhou
10. Ahmed Hosny

Papers from Haojin Yang's perspective

Ordered by how strongly the researchers Haojin Yang 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. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Dropout-GAN: Learning from a Dynamic Ensemble of Discriminators (2018) — 54 citations
• Image Captioning with Deep Bidirectional LSTMs (2016) — 299 citations
• A framework for improved video text detection and recognition (2012) — 56 citations
• Deep Learning for Medical Image Analysis (2017) — 2,676 citations