@inproceedings{5537cfde12554c6a88a4262a629204b4,
title = "Automatic Door Detection of Convenient Stores based on Association Relations",
abstract = "Although deep learning-based object detection models such as YOLOv4 performs with high accuracy and high frame rate, it was unable to distinguish between glass doors and glass walls of a convenience store. In this paper, we introduce a method that incorporates YOLOv4 and the association relations between objects in the scene to enhance the accuracy and robustness of door entrance detection of convenient stores.",
author = "Kanatip Prompol and Lin, {Chih Yang} and Somchoke Ruengittinun and Ng, {Hui Fuang} and Timothy Shih",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 8th IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021 ; Conference date: 15-09-2021 Through 17-09-2021",
year = "2021",
doi = "10.1109/ICCE-TW52618.2021.9603237",
language = "???core.languages.en_GB???",
series = "2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021",
}