Undergraduate

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MOBILE APPLICATION FOR CLASSIFICATION AND DATA COLLECTION OF CORN DISEASE USING IMAGE PROCESSING
(2024-06-11) Manahan, Jhosep B.; Perlaoan, Jelmark M.; Torne, Danna Vieyl Joy, C.
Corn (Zea mays), a significant cereal crop, is vital for livestock feed, human consumption, biofuel, and industry. However, it is vulnerable to diseases caused by bacteria, fungi, viruses, nematodes, and environmental conditions, leading to yield losses of up to 100%. In the Science City of Muñoz, traditional methods for diagnosing corn diseases are labor-intensive and error-prone. To address this, research aims to develop an Android application that uses image processing and a deep convolutional neural network (CNN) classifier to identify diseases like Gray Leaf Spot, Common Rust, and Corn Leaf Blight. The app will enable users to capture images of corn leaves for diagnosis and contribute data to a central database, facilitating proactive disease management. It incorporates GIS technology for offline functionality, supporting farmers with limited internet access and enhancing crop health and productivity