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{150943,
        author = {Anumalasetty Sri Lakshmi Thiruvalli and Anil Kumar Gupta},
        title = {Image segmentation using deep CNN to intelligently detect and access vitiligo: A survey},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {7},
        number = {11},
        pages = {46-50},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=150943},
        abstract = {Vitiligo is a disease that causes when pigment cells stop functioning. People having low vitamins will have a high chance of getting vitiligo. The national vitiligo Foundation has calculated that 0.5 to 2% of general people have vitiligo. Treatment for vitiligo is unsatisfactory. Recently, image processing is playing a key aspect in the medical field and popularly used for skin disease detections. This paper was Determining the vitiligo lesion segmented skin with the help of machine learning algorithms and convolutional neural networks (CNN'S), here Introducing a convolutional neural network that can quickly and robustly perform vitiligo skin lesion segmentation. In this paper, it presents the survey of various vitiligo detection techniques using machine learning algorithms that is based on image processing, detection, recognition of vitiligo.},
        keywords = {Vitiligo, Detection, CNN, Treatment, Machine learning algorithms.},
        month = {},
        }