Unsupervised Domain Adaptation for Image Classification and Object Detection Using Guided Transfer Learning Approach and JS Divergence

Unsupervised domain adaptation (UDA) is a transfer learning technique utilized in deep learning. UDA aims to reduce the distribution gap between labeled source and unlabeled target domains by adapting a model through fine-tuning. Typically, UDA approaches assume the same categories in both domains....

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Главные авторы:	Parth Goel, Amit Ganatra
Формат:	Artigo
Язык:	Inglês
Опубликовано:	MDPI AG 2023-04-01
Серии:	Sensors
Предметы:	domain adaptation transfer learning image classification object detection convolutional neural network deep learning
Online-ссылка:	https://www.mdpi.com/1424-8220/23/9/4436
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