Defcon27/Skin-Cancer-Classification-using-Transfer-Learning
In this paper, we have taken up the task of multi-class classification of skin lesions from dermatoscopic images in the HAM10000 dataset using deep convolutional neural networks
This project helps dermatologists and medical professionals automatically classify different types of skin lesions from dermatoscopic images. By inputting an image of a skin lesion, the system processes it to identify the lesion type, which assists in early detection and diagnosis of skin cancer. It's designed for medical practitioners who need a fast, automated second opinion on suspicious skin marks.
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Use this if you are a dermatologist or medical professional looking for an automated system to help classify skin lesions from dermatoscopic images with high accuracy.
Not ideal if you are looking for a diagnostic tool to replace professional medical judgment, as this system is designed to assist, not replace, human experts.
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Jan 25, 2023
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