Abstract: Creating a skin disease detection system using Convolutional Neural Networks (CNNs) involves leveraging deep learning techniques to classify skin conditions from images. CNNs are particularly well-suited for image recognition tasks due to their ability to automatically learn hierarchical features from data. The first step in building such a system would be to gather a dataset of skin disease images, categorized by their respective conditions. This dataset should ideally be diverse, containing images of various skin diseases, with different severities, angles, and lighting conditions to ensure robustness.

Keywords: Convolutional Neural Networks (CNN), Medical image processing, Data augmentation, Machine Learning, Deployment, Training dataset.

Cite:
B. Haritha, N. Ramya, SK. Afrin, U. Blessy Hepsibha,"Skin Disease Detection System Using Convolutional Neural Network", IARJSET International Advanced Research Journal in Science, Engineering and Technology, vol. 11, no. 3, 2024, Crossref https://doi.org/10.17148/IARJSET.2024.11348.

| DOI: 10.17148/IARJSET.2024.11348