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Autor:
Rajat Sahay, Georgi Thomas, Chowdhury Sadman Jahan, Mihir Manjrekar, Dan Popp, Andreas Savakis
Publikováno v:
Sensors, Vol 23, Iss 20, p 8409 (2023)
Unsupervised domain adaptation (UDA) aims to mitigate the performance drop due to the distribution shift between the training and testing datasets. UDA methods have achieved performance gains for models trained on a source domain with labeled data to
Externí odkaz:
https://doaj.org/article/8f375b8e724749b0a4340c417e2c6197
