MOBILE APPLICATION FOR CLASSIFICATION AND DATA COLLECTION OF CORN DISEASE USING IMAGE PROCESSING
Loading...
Date
2024-06-11
Authors
Manahan, Jhosep B.
Perlaoan, Jelmark M.
Torne, Danna Vieyl Joy, C.
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
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
Description
Keyword: