Proceedings of the 2023 International Conference on Data Science, Advanced Algorithm and Intelligent Computing (DAI 2023)

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A Depth Learning-Based Approach for Vision Prevention and Detection Utilized on Mobile Devices

Authors
Yichuan Huang1, *
1School of Information Technology, Beijing Normal University, Zhuhai, China
*Corresponding author.
Corresponding Author
Yichuan Huang
Available Online 14 February 2024.
DOI
10.2991/978-94-6463-370-2_38How to use a DOI?
Keywords
Visual Acuity Assessment; Image Processing; Deep Learning
Abstract

Vision, one of humanity’s paramount senses, plays a pivotal role in our lives and learning. Maintaining a pair of healthy eyes is of utmost significance. Conventional vision assessments typically necessitate the expertise of ophthalmologists or optometrists to diagnose myopia. Unfortunately, this approach is fraught with substantial delays. Once myopia is confirmed post-refraction, the removal of eyeglasses becomes a formidable challenge. In recent years, the prevalence of myopia, especially among school-age children, has surged, resulting in a widespread reliance on corrective lenses.The imperative for vision preservation and safeguarding has never been more apparent. In light of the rapid advancements in computer vision and artificial intelligence technologies, this paper introduces an AI-based method, designed for deployment on mobile devices, for vision prevention and assessment. Integrating artificial intelligence image processing and pattern recognition techniques, this approach enables expeditious and precise evaluation of visual acuity through analysis of the subject’s ocular images. It presents a novel solution for ocular health maintenance and disease diagnosis.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2023 International Conference on Data Science, Advanced Algorithm and Intelligent Computing (DAI 2023)
Series
Advances in Intelligent Systems Research
Publication Date
14 February 2024
ISBN
10.2991/978-94-6463-370-2_38
ISSN
1951-6851
DOI
10.2991/978-94-6463-370-2_38How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Yichuan Huang
PY  - 2024
DA  - 2024/02/14
TI  - A Depth Learning-Based Approach for Vision Prevention and Detection Utilized on Mobile Devices
BT  - Proceedings of the 2023 International Conference on Data Science, Advanced Algorithm and Intelligent Computing (DAI 2023)
PB  - Atlantis Press
SP  - 354
EP  - 368
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-370-2_38
DO  - 10.2991/978-94-6463-370-2_38
ID  - Huang2024
ER  -