Domain adaptation for object recognition using subspace sampling demons
Multimedia Tools and Applications, pp. 1-20, 2020.
Manually labeling data for training machine learning models is time-consuming and expensive. Therefore, it is often necessary to apply models built in one domain to a new domain. However, existing approaches do not evaluate the quality of intermediate features that are learned in the process of transferring from the source domain to the t...更多
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