• Ms.Anushree
• Dr. Shashidhar Kini K

Skin diseases are common worldwide, and detecting them early is important for proper treatment. This project aims to create a deep learning-based system that can identify different skin diseases by analyzing medical images. It uses convolutional neural networks (CNNs), a type of artificial intelligence, to study patterns in images and classify conditions like acne, eczema, psoriasis, and skin cancer. The system is trained with a large collection of skin images to make it accurate and reliable for diagnosing various skin problems. The system is designed to be easy to use, allowing doctors and patients to upload images and get quick results. Techniques like data augmentation and transfer learning are used to make the system work well with different skin types, image qualities, and lighting. This tool speeds up the diagnosis process, reduces costs, and can be used in remote healthcare settings. By combining technology and healthcare, the project shows how artificial intelligence can improve skin disease detection and treatment.

Deep Learning, CNN, Skin Disease, Medical Imaging, AI in Healthcare

"Skin Disease Detection with Deep Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 7, page no.1170-1174, July-2025, Available :http://www.jetir.org/papers/JETIRGX06226.pdf

"Skin Disease Detection with Deep Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 7, page no. pp1170-1174, July-2025, Available at : http://www.jetir.org/papers/JETIRGX06226.pdf