Jun Xu
Computer Vision and Pattern Recognition · with Gilmore · 2009–2016
A researcher in the Science corpus: 3 papers; trusts 8 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 26 citations into it; #21,151 of 21,575 by trust here, #8,612 by citations
- Artificial Intelligence — 23 citations into it; #34,718 of 35,345 by trust here, #12,387 by citations
Whom Jun Xu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Chih-Jen Lin
- Yoshua Bengio
- Jitendra Malik
- Yangqing Jia
- Jianbo Shi
- Xiaofeng Ren
- Geoffrey E. Hinton
- Angel Cruz-Roa
- Yann LeCun
- Alex Krizhevsky
Who trusts Jun Xu overall
- Ozan Ciga
- Dinggang Shen
- Seonwoo Min
- Shidan Wang
- Mufti Mahmud
- Justin Ker
- David Charte
- Rahul Kumar Sevakula
- Korsuk Sirinukunwattana
- Ghulam Murtaza
Papers from Jun Xu's perspective
Ordered by how strongly the researchers Jun Xu trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet Large Scale Visual Recognition Challenge
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- A Deep Convolutional Neural Network for segmenting and classifying epithelial and stromal regions in histopathological images (2016) — 458 citations
- Stacked Sparse Autoencoder (SSAE) for Nuclei Detection on Breast Cancer Histopathology Images (2015) — 815 citations
- Computer-Aided Detection and Diagnosis of Breast Cancer With Mammography: Recent Advances (2009) — 641 citations