Efficient early-stage disease detection in pomegranate (Punica granatum) using convolutional neural networks optimized by honey badger optimization algorithm

Efficient early-stage disease detection in pomegranate (Punica granatum) using convolutional neural networks optimized by honey badger optimization algorithm

This study presents a novel method for early-stage disease detection in pomegranate using a convolutional neural network (CNN) and honey badger optimization algorithm (HBOA). Existing fruit disease detection methods requires the appearance of external symptoms on the fruit surface. By the time sympt...

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Bibliographic Details
Main Authors: Sameera P, Abhay A. Deshpande
Format: Article
Language:English
Published: Taylor & Francis Group 2024-12-01
Series:Cogent Food & Agriculture
Subjects:
Pomegranate
convolutional neural network
honey badger optimization algorithm
early-stage disease detection
classification accuracy
Artificial Intelligence
Online Access:https://www.tandfonline.com/doi/10.1080/23311932.2024.2401051
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https://www.tandfonline.com/doi/10.1080/23311932.2024.2401051

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