Shichao Zhang

Computer Vision and Pattern Recognition · IEEE Transactions on Neural Networks and Learning Systems · 2002–2018

A researcher in the Science corpus: 9 papers; trusts 63 researchers and is trusted by 16 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 38 citations into it; #9,339 of 21,575 by trust here, #10,334 by citations
• Artificial Intelligence — 31 citations into it; #12,312 of 35,345 by trust here, #12,761 by citations
• Computational Mechanics — 10 citations into it
• Information Systems — 10 citations into it; #4,093 of 8,771 by trust here, #3,402 by citations
• Statistics and Probability — 10 citations into it
• Molecular Biology — 9 citations into it
• Representation & Self-Supervised Learning — 9 citations into it
• Evaluation & Benchmarks — 7 citations into it

Whom Shichao Zhang trusts overall

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

1. Xiaofeng Zhu
2. Shichao Zhang
3. Xuelong Li
4. Xiaofei He
5. Jiahua Chen
6. Geoffrey E. Hinton
7. Jason Aaron Edward Weston
8. Trevor J. Hastie
9. Robert Tibshirani
10. Jerome H. Friedman

Who trusts Shichao Zhang overall

1. Xuelian Deng
2. Plamen Parvanov Angelov
3. Mahmoud Said Elsayed
4. Pranjul Yadav
5. Yuqing Li
6. Eduardo Almeida Soares
7. S. Kotsiantis
8. Yu Zhang
9. Nhien-An Le-Khac
10. Xuelong Li

Papers from Shichao Zhang's perspective

Ordered by how strongly the researchers Shichao Zhang trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. Going deeper with convolutions

Their papers

• Efficient mining of both positive and negative association rules (2004) — 526 citations
• Efficient kNN Classification With Different Numbers of Nearest Neighbors (2018) — 1,148 citations
• Robust Joint Graph Sparse Coding for Unsupervised Spectral Feature Selection (2017) — 318 citations
• Learning k for kNN Classification (2017) — 736 citations
• Block-Row Sparse Multiview Multilabel Learning for Image Classification (2016) — 310 citations
• Efficient kNN classification algorithm for big data (2016) — 529 citations
• Decision trees with minimal costs (2004) — 323 citations
• Data preparation for data mining (2003) — 304 citations
• Association Rule Mining: Models and Algorithms (2002) — 462 citations