Yong Xia

Computer Vision and Pattern Recognition · IEEE Transactions on Medical Imaging · 2019–2021

A researcher in the Science corpus: 6 papers; trusts 467 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 93 citations into it; #14,603 of 21,575 by trust here, #11,286 by citations
• Artificial Intelligence — 78 citations into it; #26,927 of 35,345 by trust here, #19,018 by citations
• Model Architectures — 36 citations into it
• Optimization & Training — 14 citations into it
• Evaluation & Benchmarks — 9 citations into it
• Biophysics — 8 citations into it
• Media Technology — 8 citations into it

Whom Yong Xia trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Karen Simonyan
5. Diederik P. Kingma
6. Ross B. Girshick
7. Ilya Sutskever
8. Yoshua Bengio
9. Yann LeCun
10. Jia Deng

Who trusts Yong Xia overall

1. Yutong Xie
2. Ali Hatamizadeh

Papers from Yong Xia's perspective

Ordered by how strongly the researchers Yong Xia 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• CoTr: Efficiently Bridging CNN and Transformer for 3D Medical Image Segmentation (2021) — 715 citations
• COVID-19 Screening on Chest X-ray Images Using Deep Learning based Anomaly Detection (2020) — 464 citations
• Knowledge-based Collaborative Deep Learning for Benign-Malignant Lung Nodule Classification on Chest CT (2019) — 439 citations
• Medical image classification using synergic deep learning (2019) — 374 citations
• A Mutual Bootstrapping Model for Automated Skin Lesion Segmentation and Classification (2019) — 340 citations
• Attention Residual Learning for Skin Lesion Classification (2019) — 503 citations