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

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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Bibliographic Details
Main Authors: Parth Goel, Amit Ganatra
Format: Article
Language:English
Published: MDPI AG 2023-04-01
Series:Sensors
Subjects:
domain adaptation
transfer learning
image classification
object detection
convolutional neural network
deep learning
Online Access:https://www.mdpi.com/1424-8220/23/9/4436

Internet

https://www.mdpi.com/1424-8220/23/9/4436

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