Synopsis
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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Real-Time Intelligent Vegetable Grading Using YOLOv12
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LAP LAMBERT Academic Publishing, 2026
ISBN 10: 6209771254
ISBN 13: 9786209771255
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Real-Time Intelligent Vegetable Grading Using YOLOv12
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Real-Time Intelligent Vegetable Grading Using YOLOv12
Published by
LAP LAMBERT Academic Publishing Mär 2026, 2026
ISBN 10: 6209771254
ISBN 13: 9786209771255
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 72 pp. Englisch. Seller Inventory # 9786209771255
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Real-Time Intelligent Vegetable Grading Using YOLOv12 : Real-Time Vegetable Freshness and Quality Grading Using YOLO-Based Deep Learning and Computer Vision Techniques
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ISBN 13: 9786209771255
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Real-Time Intelligent Vegetable Grading Using YOLOv12 | Real-Time Vegetable Freshness and Quality Grading Using YOLO-Based Deep Learning and Computer Vision Techniques
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ISBN 10: 6209771254
ISBN 13: 9786209771255
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Taschenbuch. Condition: Neu. Real-Time Intelligent Vegetable Grading Using YOLOv12 | Real-Time Vegetable Freshness and Quality Grading Using YOLO-Based Deep Learning and Computer Vision Techniques | Senthil G A (u. a.) | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786209771255 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 135057080
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