Many-MobileNet: Multi-Model Augmentation for Robust Retinal Disease Classification

Fuente: arXiv
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Main Authors: Wang, Hao, Zhu, Wenhui, Dong, Xuanzhao, Chen, Yanxi, Li, Xin, Qiu, Peijie, Chen, Xiwen, Vasa, Vamsi Krishna, Xiong, Yujian, Dumitrascu, Oana M., Razi, Abolfazl, Wang, Yalin
Format: Preprint
Published: 2024
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author Wang, Hao
Zhu, Wenhui
Dong, Xuanzhao
Chen, Yanxi
Li, Xin
Qiu, Peijie
Chen, Xiwen
Vasa, Vamsi Krishna
Xiong, Yujian
Dumitrascu, Oana M.
Razi, Abolfazl
Wang, Yalin
author_facet Wang, Hao
Zhu, Wenhui
Dong, Xuanzhao
Chen, Yanxi
Li, Xin
Qiu, Peijie
Chen, Xiwen
Vasa, Vamsi Krishna
Xiong, Yujian
Dumitrascu, Oana M.
Razi, Abolfazl
Wang, Yalin
contents In this work, we propose Many-MobileNet, an efficient model fusion strategy for retinal disease classification using lightweight CNN architecture. Our method addresses key challenges such as overfitting and limited dataset variability by training multiple models with distinct data augmentation strategies and different model complexities. Through this fusion technique, we achieved robust generalization in data-scarce domains while balancing computational efficiency with feature extraction capabilities.
format Preprint
id arxiv_https___arxiv_org_abs_2412_02825
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Many-MobileNet: Multi-Model Augmentation for Robust Retinal Disease Classification
Wang, Hao
Zhu, Wenhui
Dong, Xuanzhao
Chen, Yanxi
Li, Xin
Qiu, Peijie
Chen, Xiwen
Vasa, Vamsi Krishna
Xiong, Yujian
Dumitrascu, Oana M.
Razi, Abolfazl
Wang, Yalin
Computer Vision and Pattern Recognition
In this work, we propose Many-MobileNet, an efficient model fusion strategy for retinal disease classification using lightweight CNN architecture. Our method addresses key challenges such as overfitting and limited dataset variability by training multiple models with distinct data augmentation strategies and different model complexities. Through this fusion technique, we achieved robust generalization in data-scarce domains while balancing computational efficiency with feature extraction capabilities.
title Many-MobileNet: Multi-Model Augmentation for Robust Retinal Disease Classification
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2412.02825