REAL-TIME OBJECT DETECTION FOR VISUALLY IMPAIRED PEOPLE
Devayani T
, Yasmine S.K.A
Object detection, Recognition, Convolutional Neural Network, YOLO algorithm, Android application.
Those who are visually impaired (VIPs) make up a sizeable segment of the population and can be found everywhere in the world. Technology has recently demonstrated its presence in every field, and cutting-edge gadgets help people in their daily lives. Our work creates a clever, intelligent system for VIPs to aid movement and guarantee their safety. The suggested method uses an automated voice to deliver real-time navigation. VIPs are able to sense and comprehend their surroundings even when they cannot see the objects around them. Also, a web-based application is created to guarantee their security. In order to develop a clever and effective object detection system, the work proposed an Android application and Convolutional Neural Network (CNN).
"REAL-TIME OBJECT DETECTION FOR VISUALLY IMPAIRED PEOPLE", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.8, Issue 7, page no.798 - 803, July-2023, Available :https://ijsdr.org/papers/IJSDR2307116.pdf
Volume 8
Issue 7,
July-2023
Pages : 798 - 803
Paper Reg. ID: IJSDR_206770
Published Paper Id: IJSDR2307116
Downloads: 000347300
Research Area: Science
Country: vellore, tamil nadu, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
