Yan Xia
Computer Vision and Pattern Recognition · with Cao · 2014–2015
A researcher in the Science corpus: 3 papers; trusts 466 researchers and is trusted by 10 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 47 citations into it; #9,639 of 21,575 by trust here, #12,992 by citations
- Artificial Intelligence — 24 citations into it; #20,682 of 35,345 by trust here, #24,417 by citations
- Evaluation & Benchmarks — 9 citations into it
- Representation & Self-Supervised Learning — 9 citations into it
- Signal Processing — 7 citations into it
- Information Retrieval & Search — 6 citations into it
- Media Technology — 6 citations into it
- Optimization & Training — 6 citations into it
Whom Yan Xia trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Geoffrey E. Hinton
- David G. Lowe
- Kaiming He
- Ilya Sutskever
- Ross B. Girshick
- Yoshua Bengio
- Matthew D. Zeiler
- Rob Fergus
- Jia Deng
Who trusts Yan Xia overall
- Xinlei Chen
- Do Hang Nga
- Görkem Algan
- Liron Bergman
- Izhak Golan
- Kuang-Huei Lee
- Stanislav Pidhorskyi
- Mohammad Sabokrou
- Christoph Baur
- Abhinav Kumar Gupta
Papers from Yan Xia's perspective
Ordered by how strongly the researchers Yan Xia 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)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet Large Scale Visual Recognition Challenge
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
Their papers
- Well Begun Is Half Done: Generating High-Quality Seeds for Automatic Image Dataset Construction from Web (2014) — 96 citations
- Learning Discriminative Reconstructions for Unsupervised Outlier Removal (2015) — 309 citations
- Sparse projections for high-dimensional binary codes (2015) — 93 citations