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@article{198708,
        author = {kalluri madhusudhan and Kasetty Parameswar Naidu and k.madhusudhan and k.pavan kumar},
        title = {Transfer learning based skin disease detection system},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {9538-9539},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=198708},
        abstract = {Skin diseases worldwide affect a large population but early detection can reduce their impact. Advances in artificial intelligence and deep learning have enabled automated medical image analysis. This paper proposes a transfer learning-based skin disease detection framework that integrates deep convolutional networks. The early detection system uses the Xception model for feature extraction and classification, along with a voting classifier for prediction. YOLOv5x6, YOLOv8, and YOLOv9 models are used for accurate lesion detection in skin care applications},
        keywords = {Transfer Learning, Skin Disease Detection, Xception, Voting Classifier, YOLO, Deep Learning, Dermoscopy, Medical Image Analysis},
        month = {April},
        }