Mingxia Liu

Artificial Intelligence · IEEE Transactions on Biomedical Engineering · 2014–2023

A researcher in the Science corpus: 7 papers; trusts 834 researchers and is trusted by 16 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 168 citations into it; #15,470 of 35,345 by trust here, #28,481 by citations
• Computer Vision and Pattern Recognition — 143 citations into it; #8,767 of 21,575 by trust here, #12,419 by citations
• Radiology, Nuclear Medicine and Imaging — 87 citations into it
• Representation & Self-Supervised Learning — 37 citations into it
• Cognitive Neuroscience — 23 citations into it
• Neurology — 18 citations into it; #1,085 of 1,455 by trust here, #861 by citations
• Biomedical Engineering — 16 citations into it
• Pulmonary and Respiratory Medicine — 16 citations into it

Whom Mingxia Liu trusts overall

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

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

Who trusts Mingxia Liu overall

1. Daochen Zha
2. Samuel Budd
3. Ugur Kursuncu
4. Chunfeng Lian
5. Zaid Pervaiz Bhat
6. Emma Claire Robinson
7. Manas Gaur
8. Erkun Yang
9. Arvid Lundervold
10. Kwei-Herng Lai

Papers from Mingxia Liu's perspective

Ordered by how strongly the researchers Mingxia Liu 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. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
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. Going deeper with convolutions

Their papers

• Hierarchical Fully Convolutional Network for Joint Atrophy Localization and Alzheimer’s Disease Diagnosis using Structural MRI (2018) — 490 citations
• Low-Rank Representation for Multi-center Autism Spectrum Disorder Identification (2018) — 21 citations
• Federated learning for medical image analysis: A survey (2023) — 434 citations
• Domain Adaptation for Medical Image Analysis: A Survey (2021) — 996 citations
• Deep Bayesian Hashing with Center Prior for Multi-modal Neuroimage Retrieval (2020) — 25 citations
• Landmark-based deep multi-instance learning for brain disease diagnosis (2017) — 398 citations
• Attribute relation learning for zero-shot classification (2014) — 49 citations