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arXiv · 2211.09064

Renewing Iterative Self-labeling Domain Adaptation with Application to the Spine Motion Prediction

Gecheng Chen·Yu Zhou·Xudong Zhang·Rui Tuo
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Abstract

The area of transfer learning comprises supervised machine learning methods that cope with the issue when the training and testing data have different input feature spaces or distributions. In this work, we propose a novel transfer learning algorithm called Renewing Iterative Self-labeling Domain Adaptation (Re-ISDA). In this work, we propose a novel transfer learning algorithm called Renewing Iterative Self-labeling Domain Adaptation (Re-ISDA).

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Gecheng Chen, Yu Zhou, Xudong Zhang, Rui Tuo. 2022-11-14. Renewing Iterative Self-labeling Domain Adaptation with Application to the Spine Motion Prediction. https://arxiv.org/abs/2211.09064

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