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@article{169920,
        author = {Vivek Nandkishor Raut and Kalpesh Joshi and Gurmeetsingh Relusinghani and Rohan Nalage and Ritik Kumar Singh and Rohan Khanna and Ruturaj Rawate},
        title = {Deep Learning Based- Smart Skin Disease Detection System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {6},
        pages = {2736-2741},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=169920},
        abstract = {This research investigates the creation of a deep learning implemented project for identifying skin diseases with the goal of improving dermatology diagnostic accessibility and accuracy. Convolutional neural networks (CNNs) are used to effectively recognize and classify in categories variety of skin disorders, such as melanoma, psoriasis, and eczema. The system is trained on an extensive dataset of dermatoscopic pictures with around 15000 images of 23 different skin diseases. This system's automated features should enable quick and accurate diagnosis, increasing access to advanced dermatological care—especially in underprivileged areas. This research aims to simplify the process of diagnosing and treating skin diseases in early stage and greatly enhance patient outcomes by fusing cutting-edge deep learning algorithms with medical imaging.},
        keywords = {Deep learning algorithms, dermatology, convolutional neural network, melanoma, eczema, psoriasis.},
        month = {November},
        }