A Novel Deep Learning Approach for Precision Agriculture: Quality Detection in Fruits and Vegetables Using Object Detection Models

A Novel Deep Learning Approach for Precision Agriculture: Quality Detection in Fruits and Vegetables Using Object Detection Models

Accurate quality detection of fruits and vegetables is crucial for optimizing harvest timing, minimizing post-harvest losses, and reducing waste. This research aims to integrate remote-sensing and deep learning (DL) technologies to develop and evaluate object detection models employing a novel DL ap...

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Bibliographic Details
Main Authors: Enoc Tapia-Mendez, Misael Hernandez-Sandoval, Sebastian Salazar-Colores, Irving A. Cruz-Albarran, Saul Tovar-Arriaga, Luis A. Morales-Hernandez
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Agronomy
Subjects:
artificial intelligence
deep learning
fruits
object detection
precision agriculture
quality
Online Access:https://www.mdpi.com/2073-4395/15/6/1307
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