Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{162034,
        author = {M.Bhumika and Bhavani Salwer and P. Bhavya Sree and C. Bhavya Sree and B.Bhumika and Bhavani Sajjanapu},
        title = {DERM-DETECT},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {7},
        pages = {286-290},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=162034},
        abstract = {This project focuses on the development of an automated system for the detection and classification of dermatological disorders using a combination of image processing techniques and machine learning algorithms. Leveraging the power of computer vision, this project aims to create a robust framework that can analyze skin images, extract relevant features, and employ machine learning models to classify different dermatological conditions.
By harnessing a diverse dataset of skin images and implementing advanced image segmentation and feature extraction methods, the system intends to achieve high accuracy in identifying disorders such as eczema, psoriasis, melanoma, lentigo and more. The outcome of this project could significantly contribute to improving the accessibility and speed of dermatological diagnosis, does not require any expensive equipment, ultimately benefiting patients and healthcare professionals alike.
},
        keywords = {},
        month = {},
        }