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@article{206279,
        author = {Juveriya Begum and Dr.C.H.Ramesh Kumar},
        title = {VerduraScan: Plant Disease Detection Using ML},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {2},
        pages = {1498-1503},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=206279},
        abstract = {Agriculture is essential for food security, but plant diseases can significantly reduce crop yield and quality. VerduraScan is a Deep Learning-based plant disease detection system that uses Convolutional Neural Networks (CNNs) to identify diseases from leaf images. Developed using Python and deployed through Streamlit, the system provides real-time disease predictions and uses Grad-CAM to highlight affected regions of the leaf for better interpretability. VerduraScan enables early disease detection, helping farmers reduce crop losses and improve agricultural productivity.},
        keywords = {Plant Disease Detection, Machine Learning, Deep Learning, Convolutional Neural Networks, Computer Vision, Agriculture, Streamlit, Grad-CAM, Image Processing, Crop Health Monitoring.},
        month = {July},
        }