SimTriplet: Simple Triplet Representation Learning with a Single GPU
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The remaining studies explored multiple other tasks and many focused on classification of malignant disorders such as breast cancer, skin cancer, and lung cancer.
“The remaining studies explored multiple other tasks and many focused on classification of malignant disorders such as breast cancer56,61,88, skin cancer89, and lung cancer59.”
From Self-supervised learning for medical image classification: a systematic review and implementation guidelines (2023) · cites this paper as [89]
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Huang, S.-C., Pareek, A., Jensen, M., Lungren, M. P., Yeung, S., & Chaudhari, A. S. (2023) · npj Digital Medicine · doi:10.1038/s41746-023-00811-0 · Cited by 479 · see citing works
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- Authors
- Liu, Q., Louis, P. C., Lu, Y., Jha, A., Zhao, M., Deng, R., Yao, T., Roland, J. T., Yang, H., Zhao, S., Wheless, L. E., & Huo, Y.
- Affiliations
- Vanderbilt University (US)
- Vanderbilt University Medical Center (US)
- Corresponding author
- Huo, Yuankai
- ORCID
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2021
- Pages
- 102-112
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W3203063869
- Cited by
- 38
- References
- 26
- Citations by year
- 2026: 3 · 2025: 2 · 2024: 7 · 2023: 7 · 2022: 18 · 2021: 1
- FWCI
- 3.81
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Licence
- Locations
- Lecture notes in computer science (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Domain Adaptation and Few-Shot Learning
- Physical Sciences › Computer Science › Artificial Intelligence › AI in cancer detection
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- contrastive learning, self-supervised learning, single-GPU training, medical image analysis, pathology images, multi-view images, unlabeled data, SimSiam
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