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@article{206720,
        author = {Alwin Solaman and Manjunath G Naik and Lochan and Dr. Suresha D},
        title = {Smart Corn Care an AI-Powered Corn Disease Detection and Management Website for Indian Farmers},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {no},
        pages = {242-251},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=206720},
        abstract = {The Corn Disease Detection System is a new automated, end-to-end deep learning framework for identifying and classifying corn plants diseases based on using Image Processing with Convolutional Neural Networks. However, inconsistent visual inspection methods, the unavailability of experts, and the difficulty of symptom identification during early stages makes diagnosis erroneous leading to huge yield loss. In response to these challenges, the proposed system integrates image acquisition, preprocessing, feature extraction, disease classification and prediction reporting in one analysis platform. Utilising a mix of architectures, augmentation methods and strong preprocessing, the system detects lesions, irregular textures, color inconstancies and disease specific characteristics with high confidence. By means of model versioning and well-formed training & evaluation cycles, it guarantees reproducibility and prediction quality. It also has a real-time prediction interface and automated reports to support data-driven decision making in crop management. Constructed with TensorFlow, Keras, OpenCV, NumPy, Flask/Streamlit & CNN-based models, our works guarantees scalability, transparency and usability within real accomplices of agricultural worlds. When tested on the Plant Village dataset and field-captured pictures, the system shows substantial enhancements in diagnostic performance the full lifecycle in which this can be used ranges from intelligent farming to early disease recognition and operational efficiency, indicating suitability for agri-advisory services, smart farm system, mobile based crop monitoring application, large scale farm management etc},
        keywords = {Machine Learning, Computer Vision, Convolutional Neural Network (CNN), Disease Classification, Deep Learning AgricultureAutomation Image Processing PlantVillage Dataset Real Time Diagnosis Smart Farming},
        month = {July},
        }