Comparing pre-trained models for efficient leaf disease detection: a study on custom CNN

Comparing pre-trained models for efficient leaf disease detection: a study on custom CNN

Abstract Leaf disease detection is a crucial task in modern agriculture, aiding in early diagnosis and prevention of crop infections. In this research paper, authors present a comprehensive study comparing nine widely used pre-trained models, namely DenseNet201, EfficientNetB3, EfficientNetB4, Incep...

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Bibliographic Details
Main Authors: Touhidul Seyam Alam, Chandni Barua Jowthi, Abhijit Pathak
Format: Article
Language:English
Published: SpringerOpen 2024-02-01
Series:Journal of Electrical Systems and Information Technology
Subjects:
Leaf disease detection
Sustainable agriculture
Data augmentation
Machine learning
Custom CNN
Convolutional Neural Network
Online Access:https://doi.org/10.1186/s43067-024-00137-1

Internet

https://doi.org/10.1186/s43067-024-00137-1

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