Identification of maize leaf diseases using red, green, blue-based images with convolutional neural network (CNN) and residual network (ResNet50) models

Identification of maize leaf diseases using red, green, blue-based images with convolutional neural network (CNN) and residual network (ResNet50) models

Maize (Zea mays) is a crucial global staple crop that serves as a primary source of food and income, especially for smallholder farmers. However, it is susceptible to diseases that drastically reduce yields if not controlled. Traditional methods of disease detection of visual inspections are often i...

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Bibliographic Details
Main Authors: Basani Lammy Nkuna, Khaled Abutaleb, Johannes George Chirima, Solomon W. Newete, Adriaan Johannes van der Walt, Adolph Nyamugama
Format: Article
Language:English
Published: Elsevier 2025-12-01
Series:Smart Agricultural Technology
Subjects:
Data augmentation
Image processing
Precision agriculture
Hyperspectral
Online Access:http://www.sciencedirect.com/science/article/pii/S2772375525004575
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