A Hybrid Machine Learning Approach for Detecting and Assessing <i>Zyginidia pullula</i> Damage in Maize Leaves

A Hybrid Machine Learning Approach for Detecting and Assessing <i>Zyginidia pullula</i> Damage in Maize Leaves

This study presents a novel approach for the detection and severity assessment of pest-induced damage in maize plants, focusing on the <i>Zyginidia pullula</i> pest. A newly developed dataset is utilized, where maize plant images are initially classified into two primary categories: heal...

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Bibliographic Details
Main Authors: Havva Esra Bakbak, Caner Balım, Aydogan Savran
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Applied Sciences
Subjects:
machine learning
deep learning
feature extraction
pest damage detection
image segmentation
hybrid classification
Online Access:https://www.mdpi.com/2076-3417/15/10/5432
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