A self-learning teacher-student framework for gastrointestinal image classification
2021 IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS)(2021)
摘要
We present a semi-supervised teacher-student framework to improve classification performance on gastrointestinal image data. As labeled data is scarce in medical settings, this framework is built specifically to take advantage of vast amounts of unlabeled data. It consists of three main steps: (1) train a teacher model with labeled data, (2) use the teacher model to infer pseudo labels with unlabe...
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关键词
Endoscopes,Hospitals,Multimedia systems,Colonoscopy,Data models,Gastrointestinal tract,Medical diagnostic imaging
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