Multi-Class Disease Detection and Wound Detection with CNN

Multi-Class Disease Detection and Wound Detection with CNN

Kavyashree.L1, Waleed Javaid Hakak2, Yashas S3 , Shamun Shaik4, Samarth Mishra5
1Kavyashree L, Computer Science & Engineering, Dayananda Sagar Academy of Technology & Management

2Waleed Javaid Hakak, Computer Science & Engineering, Dayananda Sagar Academy of Technology & Management

3Yashas S , Computer Science & Engineering, Dayananda Sagar Academy of Technology & Management

4Samarth Mishra, Computer Science & Engineering, Dayananda Sagar Academy of Technology & Management

5Shamun Shaik , Computer Science & Engineering, Dayananda Sagar Academy of Technology & Management

Abstract - This project focuses on the implementation of a deep Learning model capable of detecting skin diseases and Identifying wounds from images. By utilizing Convolutional Neural Networks (CNNs) and transfer learning, the system Classifies various skin conditions such as eczema, psoriasis, acne, and different types of wounds. The application aims to Provide preliminary diagnostics to aid dermatologists and Rural healthcare systems

Key Words: Deep Learning, Convolutional Neural Networks (CNNs), Transfer Learning, Skin Disease Detection, Wound Identification, Image Classification, Eczema, Psoriasis, Acne, Wounds, Medical Imaging, Preliminary Diagnostics, Dermatology, Rural Healthcare