Real-Time Intelligent Vegetable Grading Using YOLOv12: Real-Time Vegetable Freshness and Quality Grading Using YOLO-Based Deep Learning and Computer Vision Techniques - Brossura

G A, Senthil; J, Gowrisankar; S K, Ajaykumar

 
9786209771255: Real-Time Intelligent Vegetable Grading Using YOLOv12: Real-Time Vegetable Freshness and Quality Grading Using YOLO-Based Deep Learning and Computer Vision Techniques
Brossura
ISBN 10: 6209771254 ISBN 13: 9786209771255
Casa editrice: LAP LAMBERT Academic Publishing, 2026

Sinossi

The project focuses on developing a real-time vegetable freshness and quality grading system using advanced deep learning and computer vision techniques. By integrating the YOLOv12 object detection model with Convolutional Neural Networks (CNN), the system can accurately identify vegetables and classify them based on their freshness and quality levels. The approach leverages image processing methods to extract important features such as color, texture, and surface defects, enabling efficient grading without human intervention. This automated system improves speed, consistency, and accuracy compared to traditional manual methods, making it highly suitable for modern smart agriculture and supply chain applications. Ultimately, the proposed solution contributes to reducing food waste, enhancing quality control, and supporting sustainable agricultural practices.

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Editore
LAP LAMBERT Academic Publishing
Data di pubblicazione
2026
Lingua
Inglese
ISBN 10 
6209771254
ISBN 13 
9786209771255
Rilegatura
Copertina flessibile
Numero di pagine
72
Contatto del produttore
non disponibile
Persona responsabile
KreGa Onlinehandel GmbH
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