Xianghua Xie

Computer Vision and Pattern Recognition · 2008–2016

A researcher in the Science corpus: 3 papers; trusts 182 researchers and is trusted by 23 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 45 citations into it; #5,035 of 21,575 by trust here, #15,955 by citations
• Artificial Intelligence — 9 citations into it; #25,277 of 35,345 by trust here, #29,412 by citations
• Media Technology — 8 citations into it
• Graph Learning — 6 citations into it
• Industrial and Manufacturing Engineering — 5 citations into it; #118 of 2,521 by trust here, #1,622 by citations

Whom Xianghua Xie trusts overall

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

1. S. Li
2. Christoph Palm
3. Hui-Fuang Ng
4. David A Clausi
5. Mihran Tüceryan
6. Nebojsa Jojic
7. David G. Lowe
8. William T. Freeman
9. Yann LeCun
10. Anil K. Jain

Who trusts Xianghua Xie overall

1. Deegan Atha
2. Nirbhar Neogi
3. Ruoxu Ren
4. Francesco Bianconi
5. Nicolas Signolle
6. Tamás Czimmermann
7. Mohammad Reza Jahanshahi
8. Terence Hung
9. Dusmanta Kumar Mohanta
10. Jakob Nikolas Kather

Papers from Xianghua Xie's perspective

Ordered by how strongly the researchers Xianghua Xie 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet Large Scale Visual Recognition Challenge
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Graph Based Convolutional Neural Network (2016) — 52 citations
• A Galaxy of Texture Features (2008) — 66 citations
• A Review of Recent Advances in Surface Defect Detection using Texture analysis Techniques (2008) — 559 citations