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@article{206799,
        author = {Sonali B Naik and Aravind Naik},
        title = {AI-Based Dog Skin Disease Detection Using Deep Learning and Explainable AI},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {no},
        pages = {491-496},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=206799},
        abstract = {The system is designed for common types of skin allergies, fungal infections, and mange in dogs, which are identified based on images of the skin. To improve the clarity of the predictions, an explainable method is used to present which region in the image produces the final result. Finally, a simple web-based application is implemented to support users by uploading the images and receiving the predictions in the shortest time possible along with a visual explanation. The evaluation indicates that the performance of the model is dependent on the quality and balance of the dataset. As a result, this approach can be effective in early disease detection and assist pet owners in making timely decisions.},
        keywords = {Dog skin disease, Deep learning, MobileNetV2, Grad-CAM, Image classification},
        month = {July},
        }