Shuigeng Zhou
Computer Vision and Pattern Recognition · 2009–2017
A researcher in the Science corpus: 4 papers; trusts 24 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 34 citations into it
- Molecular Biology — 28 citations into it
- Artificial Intelligence — 19 citations into it; #27,859 of 35,345 by trust here, #34,213 by citations
- Computational Theory and Mathematics — 12 citations into it
- Computational Biology & Bioinformatics — 10 citations into it
Whom Shuigeng Zhou trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Who trusts Shuigeng Zhou overall
Papers from Shuigeng Zhou's perspective
Ordered by how strongly the researchers Shuigeng Zhou 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
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Learning Multiple Layers of Features from Tiny Images
- ImageNet: A large-scale hierarchical image database
Their papers
- A new taxonomy-based protein fold recognition approach based on autocross-covariance transformation (2009) — 186 citations
- Boosting compound-protein interaction prediction by deep learning (2015) — 164 citations
- Exploiting Twitter Moods to Boost Financial Trend Prediction Based on Deep Network Models (2016) — 17 citations
- Focusing Attention: Towards Accurate Text Recognition in Natural Images (2017) — 493 citations