Hui Ma

Computer Vision and Pattern Recognition · with Deng · 2020

A researcher in the Science corpus: 2 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 10 citations into it

Whom Hui Ma trusts

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

1. Thomas Brox (in Computer Vision and Pattern Recognition)
2. Philipp Fischer (in Computer Vision and Pattern Recognition)

Papers from Hui Ma's perspective

Ordered by how strongly the researchers Hui Ma 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. U-Net: Convolutional Networks for Biomedical Image Segmentation (International Conference on Medical Image Computing and Computer-Assisted Intervention)
4. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
5. PyTorch: An Imperative Style, High-Performance Deep Learning Library
6. Learning Deep Features for Discriminative Localization
7. Is object localization for free? - Weakly-supervised learning with convolutional neural networks
8. Dermatologist-level classification of skin cancer with deep neural networks
9. [Asymptomatic infection of COVID-19 and its challenge to epidemic prevention and control]. (Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi)
10. Outbreak of pneumonia of unknown etiology in Wuhan, China: The mystery and the miracle (Journal of Medical Virology)

Their papers

• A Weakly-Supervised Framework for COVID-19 Classification and Lesion Localization From Chest CT (2020) — 534 citations
• Deep Learning-based Detection for COVID-19 from Chest CT using Weak Label (2020) — 614 citations