@inproceedings{8a1aff3afa984b83a18404c993b7cdbd,
title = "A Safety System for Industrial Fields using YOLO Object Detection with Deep Learning",
abstract = "This paper proposes a safety system that can be used in various industrial field situations. The safety system detects boundaries with a line detection method and identifies people using YOLO (You Only Look Once) from images captured through a camera. And using the depth image, this system determines which individuals are within the danger range among the detected people. Therefore, this paper includes the selection of a specific YOLO model, performance improvement through training YOLO models with deep learning, depth data correction, line detection method, and system optimization in the proposed hardware.",
keywords = "Deep learning, Industrial safety, Open-cv, Safety system, YOLO",
author = "Rhee, \{Jeong Yoon\} and Park, \{Jun Hyuk\} and Lee, \{Jae In\} and Ahn, \{Hyun Tae\} and Pham, \{Long Hoang\} and Jeon, \{Jae Wook\}",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 International Technical Conference on Circuits/Systems, Computers, and Communications, ITC-CSCC 2023 ; Conference date: 25-06-2023 Through 28-06-2023",
year = "2023",
doi = "10.1109/ITC-CSCC58803.2023.10210722",
language = "English",
series = "2023 International Technical Conference on Circuits/Systems, Computers, and Communications, ITC-CSCC 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2023 International Technical Conference on Circuits/Systems, Computers, and Communications, ITC-CSCC 2023",
}