Comparison of Convolutional Neural Network Architectures for Classification of Tomato Plant Diseases

Comparison of Convolutional Neural Network Architectures for Classification of Tomato Plant Diseases

Tomato plants are highly affected by diverse diseases. A timely and accurate diagnosis plays an important role to prevent the quality of crops. Recently, deep learning (DL), specifically convolutional neural networks (CNNs), have achieved extraordinary results in many applications, including the cla...

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Bibliographic Details
Main Authors: Valeria Maeda-Gutiérrez, Carlos E. Galván-Tejada, Laura A. Zanella-Calzada, José M. Celaya-Padilla, Jorge I. Galván-Tejada, Hamurabi Gamboa-Rosales, Huizilopoztli Luna-García, Rafael Magallanes-Quintanar, Carlos A. Guerrero Méndez, Carlos A. Olvera-Olvera
Format: Article
Language:English
Published: MDPI AG 2020-02-01
Series:Applied Sciences
Subjects:
tomato plant diseases
deep learning
convolutional neural networks
classification
Online Access:https://www.mdpi.com/2076-3417/10/4/1245

Internet

https://www.mdpi.com/2076-3417/10/4/1245

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