Research on detection ability of cigarette package appearance detection device

Ting Yao; Bo Liu; Dong Yan; Dongfeng Li; Yanbin Li

doi:10.1117/12.3029011

22 May 2024 Research on detection ability of cigarette package appearance detection device

Ting Yao, Bo Liu, Dong Yan, Dongfeng Li, Yanbin Li

Proceedings Volume 13176, Fourth International Conference on Machine Learning and Computer Application (ICMLCA 2023); 131762R (2024) https://doi.org/10.1117/12.3029011
Event: Fourth International Conference on Machine Learning and Computer Application (ICMLCA 2023), 2023, Hangzhou, China

Abstract

In this paper, the problem of nonstandard samples of cigarette packet found in daily patrol inspection is taken as the starting point. Based on the research of equipment testing principle, we designed a method to obtain the minimum detection limit of the cigarette package appearance detection device. Through a large number of simulation experiments, accurate and reliable experimental data conclusions are obtained, the quantitative evaluation of the detection capability of the cigarette packet appearance detection device is realized, and provided a quantitative reference for the validity verification of the cigarette package appearance detection device.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Ting Yao, Bo Liu, Dong Yan, Dongfeng Li, and Yanbin Li "Research on detection ability of cigarette package appearance detection device", Proc. SPIE 13176, Fourth International Conference on Machine Learning and Computer Application (ICMLCA 2023), 131762R (22 May 2024); https://doi.org/10.1117/12.3029011

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available