A Machine Learning Approached Model to Identify the Object for Visually Impaired Person
Sunita Joshi, Neha Gupta, Mitali, Gautam Yadav · 2023
According to the World Health Organization (WHO), 253 million individuals worldwide are visually impaired, including 36 million who are blind and 217 million who have moderate to severe vision impairment. The objective of this study is to demonstrate an improved approach through a real-time working model that is used for the prediction of objects around a visually impaired person. The proposed model is based on object detection which aids in several aspects of object prediction such as accident reduction and managing daily routines while protecting themselves from hazards or obstacles. The proposed model has an accuracy of 72%. More datasets will be embedded in the future to conduct large-scale object prediction with greater accuracy.