Enhancing Grapevine Node Detection to Support Pruning Automation: Leveraging State-of-the-Art YOLO Detection Models for 2D Image Analysis

Enhancing Grapevine Node Detection to Support Pruning Automation: Leveraging State-of-the-Art YOLO Detection Models for 2D Image Analysis

Automating pruning tasks entails overcoming several challenges, encompassing not only robotic manipulation but also environment perception and detection. To achieve efficient pruning, robotic systems must accurately identify the correct cutting points. A possible method to define these points is to...

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Bibliographic Details
Main Authors: Francisco Oliveira, Daniel Queirós da Silva, Vítor Filipe, Tatiana Martins Pinho, Mário Cunha, José Boaventura Cunha, Filipe Neves dos Santos
Format: Article
Language:English
Published: MDPI AG 2024-10-01
Series:Sensors
Subjects:
deep learning
precision agriculture
pruning
robotic systems
YOLO
Online Access:https://www.mdpi.com/1424-8220/24/21/6774
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