Enhui Yang

Computer Vision and Pattern Recognition · 2017

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 15 citations into it

Whom Enhui Yang trusts overall

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

1. Chih-Jen Lin
2. Geoffrey E. Hinton
3. Alex Krizhevsky

Papers from Enhui Yang's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Gradient-based learning applied to document recognition
3. Going deeper with convolutions
4. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
5. Understanding the difficulty of training deep feedforward neural networks
6. Visualizing and Understanding Convolutional Networks
7. Fully convolutional networks for semantic segmentation
8. Improving neural networks by preventing co-adaptation of feature detectors
9. OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks
10. Deep Learning

Their papers

• Automated Pixel‐Level Pavement Crack Detection on 3D Asphalt Surfaces Using a Deep‐Learning Network (2017) — 900 citations