Lijun Zhao
Computer Vision and Pattern Recognition · 2014–2019
A researcher in the Science corpus: 4 papers; trusts 424 researchers and is trusted by 24 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 102 citations into it; #5,247 of 21,575 by trust here, #8,502 by citations
- Media Technology — 53 citations into it; #529 of 3,621 by trust here, #789 by citations
- Artificial Intelligence — 22 citations into it
- Remote Sensing — 18 citations into it; #32 of 95 by trust here, #70 by citations
- Information Retrieval & Search — 6 citations into it
- Aerospace Engineering — 5 citations into it
- Evaluation & Benchmarks — 5 citations into it
- Model Architectures — 5 citations into it
Whom Lijun Zhao trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Thorsten Joachims
- David G. Lowe
- Chih-Jen Lin
- Svetlana Lazebnik
- Yi Yang
- Cordelia Schmid
- Alex Krizhevsky
- Geoffrey E. Hinton
- Kaiming He
- Andrew Zisserman
Who trusts Lijun Zhao overall
- Gui-Song Xia
- Nassim Ammour
- Jingwen Hu
- Bei Zhao
- Fan Hu
- Gong Cheng
- Ping Tang
- Liangpei Zhang
- Yanfei Zhong
- Baochang Zhang
Papers from Lijun Zhao's perspective
Ordered by how strongly the researchers Lijun Zhao 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)
- ImageNet: A large-scale hierarchical image database
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- Remote Sensing Image Scene Classification Using CNN-CapsNet (2019) — 362 citations
- Feature significance-based multibag-of-visual-words model for remote sensing image scene classification (2016) — 126 citations
- A 2-D wavelet decomposition-based bag-of-visual-words model for land-use scene classification (2014) — 71 citations
- Land-Use Scene Classification Using a Concentric Circle-Structured Multiscale Bag-of-Visual-Words Model (2014) — 163 citations