Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

Identification of Maize Leaf Diseases Based On AlexNet and ResNet50 Convolutional Neural Networks

Domaine:

agriculture

Type de record:

paper
Créateur:
MauRaeCyrBoa
Éditeur:
STM
Hôte:
Maize crop protection is crucial for global food security, requiring accurate disease identification. In Kenya, farmers rely on subjective visual analysis of symptomatic leaves, which is time-consuming and prone to errors. Computer vision technologies, like deep learning and machine learning, offer promising solutions for disease identification. This study applies Convolutional Neural Networks (CNNs), specifically AlexNet and ResNet-50, to automatically learn image features and enhance speed and accuracy in maize leaf disease identification. A dataset of 3200 digital maize leaf disease images from Embu County is used for training and testing. AlexNet achieved the highest average accuracy of 98.3%, followed by ResNet-50 at 96.6%. The machine learning, support vector machine (SVM) exhibited the lowest average accuracy of 85.5%. These findings highlight the significance of utilizing AlexNet and ResNet-50 in maize leaf disease identification and classification.

Visit

doi.org

Tasks

computer visionimage classification

Licenses

https://creativecommons.org/licenses/by-sa/4.0

Similaires

Classification of Multiple Maize Leaf Diseases Using a Blended Convolutional Neural NetworkConvolutional Neural Network Based Maize Plant Disease IdentificationUtilizing Convolutional Neural Networks for Accurate Detection of Leaf Diseases in Fava BeansMobile app-based tomato disease identification with fine-tuned convolutional neural networksLanguage Identification Using Deep Convolutional Recurrent Neural NetworksEarly Detection and Classification of Potato Leaf Disease Using Convolutional Neural Networks

Classification of Multiple Maize Leaf Diseases Using a Blended Convolutional Neural Network

Convolutional Neural Network Based Maize Plant Disease Identification

Utilizing Convolutional Neural Networks for Accurate Detection of Leaf Diseases in Fava Beans

Background: Worldwide, people appreciate the variety of faba beans, also referred to as broad beans.

Mobile app-based tomato disease identification with fine-tuned convolutional neural networks

Language Identification Using Deep Convolutional Recurrent Neural Networks

Language Identification (LID) systems are used to classify the spoken language from a given audio sa

Early Detection and Classification of Potato Leaf Disease Using Convolutional Neural Networks

Potato farming faces significant challenges due to the prevalence of leaf diseases, which lead to su