Decoupled Unbiased Teacher for Source-Free Domain Adaptive Medical Object Detection

Source-free domain adaptation (SFDA) aims to adapt a lightweight pretrained source model to unlabeled new domains without the original labeled source data. Due to the privacy of patients and storage consumption concerns, SFDA is a more practical setting for building a generalized model in medical ob...

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Veröffentlicht in:	IEEE transaction on neural networks and learning systems 2024-06, Vol.35 (6), p.7287-7298
Hauptverfasser:	Liu, Xinyu, Li, Wuyang, Yuan, Yixuan
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptation Adaptation models Algorithms Bias Data models Feature extraction Humans Labels Machine Learning Medical diagnostic imaging Medical object detection Neural Networks, Computer Object detection Object recognition Pattern Recognition, Automated - methods Predictive models self-supervised learning source-free domain adaptation (SFDA) structural causal model (SCM) Task analysis Teachers
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