TY - GEN
T1 - A hybrid intelligent system for assisting low-vision people with over-the-counter medication
AU - Leung, Man Fai
AU - Che, Hangjun
AU - Kwok, Chin Hung
AU - Chan, Lewis
N1 - Funding Information:
This work was supported by the Fundamental Research Funds for the Central Universities (Grant No.SWU020006), National Natural Science Foundation of China (Grant No.62003281), Natural Science Foundation of Chongqing, China(Grant No. cstc2021jcyj-msxmX1169).
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Because people with low vision have difficulty pur-chasing and taking the correct medicine and dosages on time, this paper presents a system with a Flask Server and Android application that assists low-vision people with using over-the-counter (OTC) medication correctly. The system is mainly divided into three parts: an Android application, a Flask server and a MongoDB database. The application provides a medication time reminder, medicine information retrieval and image capture for recognition functions. A server recognizes the medication package by combining optical character recognition (OCR) and an image classification convolutional neural network (CNN). A database is used to store and provide medicine information. The experimental results show that the recognition performance has up to 96.1% accuracy. Moreover, the approach is shown to be able to handle out-of-distribution images.
AB - Because people with low vision have difficulty pur-chasing and taking the correct medicine and dosages on time, this paper presents a system with a Flask Server and Android application that assists low-vision people with using over-the-counter (OTC) medication correctly. The system is mainly divided into three parts: an Android application, a Flask server and a MongoDB database. The application provides a medication time reminder, medicine information retrieval and image capture for recognition functions. A server recognizes the medication package by combining optical character recognition (OCR) and an image classification convolutional neural network (CNN). A database is used to store and provide medicine information. The experimental results show that the recognition performance has up to 96.1% accuracy. Moreover, the approach is shown to be able to handle out-of-distribution images.
KW - CNN
KW - image classification
KW - low vision
KW - over-the-counter
UR - https://www.scopus.com/pages/publications/85142666219
U2 - 10.1109/ICIST55546.2022.9926891
DO - 10.1109/ICIST55546.2022.9926891
M3 - Conference contribution
AN - SCOPUS:85142666219
T3 - 2022 12th International Conference on Information Science and Technology, ICIST 2022
SP - 38
EP - 44
BT - 2022 12th International Conference on Information Science and Technology, ICIST 2022
T2 - 12th International Conference on Information Science and Technology, ICIST 2022
Y2 - 14 October 2022 through 16 October 2022
ER -