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Research Paper | Computer Science & Engineering | India | Volume 14 Issue 1, January 2025 | Popularity: 4.8 / 10
Enhancing Medical Image Classification with Vision Transformers on Diverse Datasets
Aditya Dhar Dwivedi
Abstract: Medical image classification is essential for accurate diagnosis and effective treatment planning. This research investigates the implementation of MedViT, a robust Vision Transformer tailored for medical image analysis, and compares its performance against four models: StarterNet, TinyVGG, a standard Vision Transformer (ViT), and a Convolutional Neural Network (CNN). Evaluations conducted on PathMINST, a medical imaging dataset, and CIFAR - 10, a general - purpose image classification dataset, to assess model generalization.
Keywords: MedViT, Vision Transformer, Medical Image Classification, PathMINST, CIFAR-10
Edition: Volume 14 Issue 1, January 2025
Pages: 680 - 693
DOI: https://www.doi.org/10.21275/SR25113171116
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