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Classifying skin lesion with CNN architecture (EfficientNet-B3, VGG16, DenseNet, Inception V3)

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NushaMBZ/Skin-Lesion-Classification-with-CNN

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This repository focuses on the application of Convolutional Neural Network (CNN) architectures for the classification of skin lesions. Four popular CNN models, namely EfficientNet-B3, VGG16, DenseNet, and Inception V3, have been implemented and evaluated on a dataset of skin lesion images.

Results

Phase 01

Models Base Model EfficientNet-B3 VGG16 DenseNet Inception V3
Data Augmentation False False False False False
Parameters 85,867 10,783,535 14,716,227 12,647,875 21,808,931
Depth 10 5 7 8 7
Validation 68% 72% 68% 73% 71%
Link BM EFB3 VGG16 IV3

Dataset

Melanoma Detection Dataset

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Classifying skin lesion with CNN architecture (EfficientNet-B3, VGG16, DenseNet, Inception V3)

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