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Eye diseases usually cause blindness and visual impairment. As per the statistics, there are over 285 million visually impaired people living worldwide. They come across many troubles in their daily life, especially while navigating from one place to another on their own. They often depend on others for help to satisfy their day-to-day needs. So, it is quite a challenging task to implement a technological solution to assist them. Several technologies were developed for the assistance of visually impaired people. One such attempt is that we would wish to make an Integrated Machine Learning System that allows the blind victims to identify and classify real-time objects generating voice feedback and distance. Which also produces warnings whether they are very close or far away from the thing.
K Sahaja. 2026. \u201cBlind Assistance System using Image Processing\u201d. Global Journal of Computer Science and Technology - D: Neural & AI GJCST-D Volume 22 (GJCST Volume 22 Issue D2): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
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Total Score: 105
Country: India
Subject: Global Journal of Computer Science and Technology - D: Neural & AI
Authors: K Sahaja, P. Rama Devi, S. Santrupth, M. P. Tony Harsha, K. Balasubramanyam Reddy (PhD/Dr. count: 0)
View Count (all-time): 298
Total Views (Real + Logic): 2866
Total Downloads (simulated): 56
Publish Date: 2026 01, Fri
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Eye diseases usually cause blindness and visual impairment. As per the statistics, there are over 285 million visually impaired people living worldwide. They come across many troubles in their daily life, especially while navigating from one place to another on their own. They often depend on others for help to satisfy their day-to-day needs. So, it is quite a challenging task to implement a technological solution to assist them. Several technologies were developed for the assistance of visually impaired people. One such attempt is that we would wish to make an Integrated Machine Learning System that allows the blind victims to identify and classify real-time objects generating voice feedback and distance. Which also produces warnings whether they are very close or far away from the thing.
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