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...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Foods Ročník 11; číslo 15; s. 2197
Hlavní autoři:	Yang, Ke, Peng, Baoliang, Gu, Fengwei, Zhang, Yanhua, Wang, Shenying, Yu, Zhaoyang, Hu, Zhichao
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Basel MDPI AG 24.07.2022 MDPI
Témata:	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
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!