Ming Zong

Computer Vision and Pattern Recognition · 2016–2018

A researcher in the Science corpus: 3 papers; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 20 citations into it
• Artificial Intelligence — 17 citations into it

Whom Ming Zong trusts overall

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

1. Xiaofeng Zhu
2. Shichao Zhang
3. Xuelong Li
4. Chih-Jen Lin

Papers from Ming Zong's perspective

Ordered by how strongly the researchers Ming Zong 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. Gradient-based learning applied to document recognition
4. LIBSVM: A library for support vector machines
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Going deeper with convolutions
9. ImageNet: A large-scale hierarchical image database
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Efficient kNN Classification With Different Numbers of Nearest Neighbors (2018) — 1,148 citations
• Learning k for kNN Classification (2017) — 736 citations
• Efficient kNN classification algorithm for big data (2016) — 529 citations