Consideration of image recognition results for automatic wood ear mushroom harvesting with YOLOv7
大島商船高等専門学校紀要 Volume 56
Page 8-12
published_at 2023-12
Title
YOLOv7によるキクラゲ自動収穫のための画像認識結果の一考察
Consideration of image recognition results for automatic wood ear mushroom harvesting with YOLOv7
Source Identifiers
[PISSN] 0387-9232
[NCID] AN00031668
Creator Keywords
smart agriculture
automatic harvesting system
deep learning
you only look once
In recent years, the scarcity of successors for farmers in Japan has emerged as a pressing problem. This issue has drawn the attention of researchers, pushing towards smart agriculture by utilizing robots and other cutting-edge technologies. With cooperation from a local producer, the research team is developing an automated Wood Ear Mushroom harvesting system. In this study, the author conducted an experiment to confirm the extent to which recognition accuracy could be improved by switching the detection algorithm from YOLOv4 to YOLOv7. The results indicated a recognition accuracy improvement of more than 10%.
Resource Type
departmental bulletin paper
Publishers
National Institute of Technology,Oshima College
Date Issued
2023-12
File Version
Version of Record
Access Rights
open access
Relations
[ISSN]0387-9232
[NCID]AN00031668