An enhanced synthetic oversampling framework with self-supervised contrastive learning for multi-class image imbalance

Class imbalance significantly affects the performance of machine learning and deep learning classifiers, especially in image recognition tasks where certain classes are underrepresented. Traditional synthetic oversampling methods, while helpful, often fail to address the complexities of real-world d...

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Bibliographic Details
Main Author: Xiaoling, Gao
Format: Thesis
Language:en
Published: 2025
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/132623/1/132623.pdf
https://ir.uitm.edu.my/id/eprint/132623/
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