Ruijia Xu
Computer Vision and Pattern Recognition · 2017–2019
A researcher in the Science corpus: 4 papers; trusts 534 researchers and is trusted by 19 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 103 citations into it; #6,855 of 21,575 by trust here, #6,873 by citations
- Artificial Intelligence — 87 citations into it; #9,844 of 35,345 by trust here, #10,430 by citations
- Representation & Self-Supervised Learning — 50 citations into it
- Model Architectures — 15 citations into it
- Cancer Research — 9 citations into it
- Optimization & Training — 9 citations into it
- Radiology, Nuclear Medicine and Imaging — 7 citations into it; #584 of 3,265 by trust here, #1,233 by citations
- Signal Processing — 7 citations into it
Whom Ruijia Xu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Kaiming He
- Alex Krizhevsky
- Yoshua Bengio
- Yann LeCun
- Diederik P. Kingma
- Ilya Sutskever
- Ross B. Girshick
- Karen Simonyan
- Mingsheng Long
Who trusts Ruijia Xu overall
- Jian Liang
- Dapeng Hu
- Xingchao Peng
- Ying Jin
- Hui Tang
- Garrett Wilson
- Toshihiko Matsuura
- Kuniaki Saito
- Fabio Maria Carlucci
- Yongchun Zhu
Papers from Ruijia Xu's perspective
Ordered by how strongly the researchers Ruijia 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)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- Deep Cocktail Network: Multi-source Unsupervised Domain Adaptation with Category Shift (2018) — 437 citations
- Larger Norm More Transferable: An Adaptive Feature Norm Approach for Unsupervised Domain Adaptation (2018) — 574 citations
- Multi-label Image Recognition by Recurrently Discovering Attentional Regions (2017) — 334 citations
- ClusterNet: Deep Hierarchical Cluster Network With Rigorously Rotation-Invariant Representation for Point Cloud Analysis (2019) — 189 citations