Convolutional Neural Network for Object Detection in Garlic Root Cutting Equipment

Traditional manual garlic root cutting is inefficient and can cause food safety problems. To develop food processing equipment, a novel and accurate object detection method for garlic using deep learning—a convolutional neural network—is proposed in this study. The you-only-look-once (YOLO) algorith...

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Bibliographic Details
Published in:	Foods Vol. 11; no. 15; p. 2197
Main Authors:	Yang, Ke, Peng, Baoliang, Gu, Fengwei, Zhang, Yanhua, Wang, Shenying, Yu, Zhaoyang, Hu, Zhichao
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 24.07.2022 MDPI
Subjects:	Accuracy Algorithms Artificial neural networks bulbs Computer vision convolutional neural network Cutting equipment Deep learning Efficiency Food processing food research Food safety food safety control Food science Garlic garlic root cutting Harvest Machine learning Neural networks object detection Object recognition Physiological aspects Sensors standard deviation Transfer learning YOLO United Kingdom
ISSN:	2304-8158, 2304-8158
Online Access:	Get full text
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