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@article{159584,
        author = {ANSARI SAUD AHMED and KHAN ZAID and RUSSEL FERNANDES and JAYA JESWANI},
        title = {Corn Leaf Disease Detection Using Deep Learning },
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {12},
        pages = {290-295},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=159584},
        abstract = {The leaf disease detection system is designed to identify and provide a solution for any disease that may be present in a leaf or plant. This is especially crucial in developing countries where agriculture plays a significant role, and it is essential to recognize unhealthy plant leaves and classify the disease to prevent significant loss of plants. By providing faster and more accurate results, farmers can reduce their losses. The process of discovering the type of disease involves four stages: image pre-processing, feature extraction, and classification. Image pre-processing is used to enhance the quality of the image, and for classification, a Convolution Neural Network (CNN) is utilized, which includes various layers that aid in prediction. Finally, a cure is suggested to the user during the terminal stage},
        keywords = {Convolutional neural network (CNN), Feature Extraction, Classification},
        month = {},
        }