Xiwen Yao

Computer Vision and Pattern Recognition · 2013–2022

A researcher in the Science corpus: 9 papers; trusts 858 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 304 citations into it; #7,938 of 21,575 by trust here, #5,711 by citations
• Media Technology — 105 citations into it; #1,251 of 3,621 by trust here, #559 by citations
• Artificial Intelligence — 87 citations into it; #32,598 of 35,345 by trust here, #20,836 by citations
• Remote Sensing — 25 citations into it
• Model Architectures — 20 citations into it
• Ocean Engineering — 14 citations into it
• Representation & Self-Supervised Learning — 14 citations into it
• Optimization & Training — 11 citations into it

Whom Xiwen Yao trusts overall

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

1. Ross B. Girshick
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Kaiming He
5. Yi Yang
6. Gong Cheng
7. Karen Simonyan
8. Yann LeCun
9. Yoshua Bengio
10. Ilya Sutskever

Who trusts Xiwen Yao overall

1. Gong Cheng
2. Junwei Han
3. Peicheng Zhou
4. Yang Long
5. Kumar Ayush
6. Xiaoqiang Lu
7. Muhammad Hussain
8. Jian Kang
9. Marc Rußwurm
10. Yiping Gong

Papers from Xiwen Yao's perspective

Ordered by how strongly the researchers Xiwen Yao trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. ImageNet: A large-scale hierarchical image database
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Attention is All you Need (Neural Information Processing Systems)
6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. Gradient-based learning applied to document recognition
8. Long Short-Term Memory
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Towards Large-Scale Small Object Detection: Survey and Benchmarks (2022) — 694 citations
• Oriented R-CNN for Object Detection (2021) — 1,161 citations
• When Deep Learning Meets Metric Learning: Remote Sensing Image Scene Classification via Learning Discriminative CNNs (2018) — 1,041 citations
• Scene classification of high resolution remote sensing images using convolutional neural networks (2016) — 80 citations
• Object detection in VHR optical remote sensing images via learning rotation-invariant HOG feature (2016) — 33 citations
• Semantic Annotation of High-Resolution Satellite Images via Weakly Supervised Learning (2016) — 325 citations
• A coarse-to-fine model for airport detection from remote sensing images using target-oriented visual saliency and CRF (2015) — 87 citations
• Semantic Segmentation based on Stacked Discriminative Autoencoders and Context-Constrained Weakly Supervised Learning (2015) — 11 citations
• Object detection in remote sensing imagery using a discriminatively trained mixture model (2013) — 164 citations