Deep Learning-Based Solution for Differently-Abled Persons in The Society

Rahul. M, R. P, Mohammed Mubashir Yakoobi, N. Gowda
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Abstract

This paper intends to furnish support to individuals grappling with visual impairments through the employment of YOLOV4, an advanced object detection model. The proposed system employs a mobile application to generate audio feedback in real-time contingent upon object detection in the user’s immediate surroundings. YOLOV4’s remarkable precision in detecting objects renders it an ideal contender for this application. The effectiveness of the system will be evaluated through a series of experiments, and its potential impact on the visually impaired community will be analyzed. This paper represents a breakthrough in assistive technology, and can potentially transform the lives of millions of people worldwide. Overall, this paper aims to harness cutting-edge technology to enhance the quality of life for individuals with visual impairments by enabling them to better navigate their surroundings through the use of audio feedback.
基于深度学习的社会残疾人解决方案
本文旨在通过使用先进的目标检测模型YOLOV4,为视觉障碍患者提供支持。该系统采用移动应用程序,根据用户周围环境中的物体检测实时生成音频反馈。YOLOV4在检测对象方面的卓越精度使其成为此应用程序的理想竞争者。通过一系列的实验来评估该系统的有效性,并分析其对视障群体的潜在影响。这篇论文代表了辅助技术的一个突破,并有可能改变全世界数百万人的生活。总的来说,这篇论文的目的是利用尖端技术来提高视力障碍患者的生活质量,使他们能够通过使用音频反馈来更好地导航周围的环境。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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