SSCLNet: A Self-Supervised Contrastive Loss-Based Pre-Trained Network for Brain MRI Classification

SSCLNet: A Self-Supervised Contrastive Loss-Based Pre-Trained Network for Brain MRI Classification

Brain magnetic resonance images (MRI) convey vital information for making diagnostic decisions and are widely used to detect brain tumors. This research proposes a self-supervised pre-training method based on feature representation learning through contrastive loss applied to unlabeled data. Self-su...

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Bibliographic Details
Main Authors:	Animesh Mishra, Ritesh Jha, Vandana Bhattacharjee
Format:	Article
Language:	English
Published:	IEEE 2023-01-01
Series:	IEEE Access
Subjects:	Contrastive learning convolutional neural networks pre-training ResNet self-supervised
Online Access:	https://ieeexplore.ieee.org/document/10018340/

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