Fuzzy deep learning architecture for cucumber plant disease detection and classification

Fuzzy deep learning architecture for cucumber plant disease detection and classification

Abstract This paper introduces a novel fuzzy deep convolutional neural network architecture for cucumber plant disease detection, contributing to precision farming in Industry 5.0. The proposed architecture incorporates 40 convolutional layers, 4 pooling layers, 4 inverted bottleneck blocks, 4 bottl...

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Bibliographic Details
Main Authors: Anas Bilal, Junaid Ali Khan, Abdulkareem Alzahrani, Khalid Almohammadi, Maha Alamri, Xiaowen Liu
Format: Article
Language:English
Published: SpringerOpen 2025-05-01
Series:Journal of Big Data
Subjects:
Remote sensing dataset
Fuzzy deep learning architecture
Cucumber plant disease dataset
Feature selection
Chaotic particle swarm optimization
Monte Carlo simulations
Online Access:https://doi.org/10.1186/s40537-025-01156-z
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https://doi.org/10.1186/s40537-025-01156-z

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