Android Application for Object Recognition Using Neural Networks for the Visually Impaired

Dosi, Sanika; Sambare, S. S.; Singh, Shashank; Lokhande, Netra; Garware, Bhushan

doi:10.1109/iccubea.2018.8697886

Cited by 5 publications

(2 citation statements)

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“…An Android software created by Dosi et al [14] uses the phone's camera to recognise objects in real-time and pronounce the thing to the visually impaired user as feedback. They chose a convolutional neural network-based deep learning technique for better recognition and quicker reaction times.…”

Section: Android Application For Object Recognition Using Neural Netw...mentioning

confidence: 99%

Obstacle Detection and Distance Estimation for Visually Impaired People

Leong,

Ramasamy

2023

IEEE Access

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In the realm of assistive technologies for visually impaired persons (VIPs), existing solutions such as white canes and guide dogs have limitations in range and practicality. Moreover, current electronic systems often fall short in terms of portability and the ability to estimate distances in real-time. To bridge these gaps, this study introduces a revolutionary wearable device comprising a Raspberry Pi, a camera module, and a pretrained convolutional neural network, all integrated into a pair of smart glasses. These glasses are designed to identify objects and estimate their distances from the wearer, providing real-time auditory or haptic feedback. The development process was rigorous, involving the deployment of machine learning algorithms for object identification and the integration of camera and sensor technology into a lightweight, user-friendly frame. The system's performance was extensively evaluated using quantitative metrics, showing its precision, speed, and usability. Conclusively, this study presents a significant leap in wearable assistive technologies, offering enhanced spatial awareness, autonomy, and quality of life for VIPs.

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Section: Android Application For Object Recognition Using Neural Netw...mentioning

confidence: 99%

Obstacle Detection and Distance Estimation for Visually Impaired People

Leong,

Ramasamy

2023

IEEE Access

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“…Nevertheless, this approach is usually confined to a limited number of objects due to hardware limitations. Dosi et al [44] made an android app for VI people that locally recognizes objects. They used MobileNets [45] for object recognition which is a neural network for mobile and embedded vision applications.…”

Section: Object Recognitionmentioning

confidence: 99%

Recent trends in computer vision-driven scene understanding for VI/blind users: a systematic mapping

Valipoor

Jiménez

2022

Univ Access Inf Soc

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During the past years, the development of assistive technologies for visually impaired (VI)/blind people has helped address various challenges in their lives by providing services such as obstacle detection, indoor/outdoor navigation, scene description, text reading, facial recognition and so on. This systematic mapping review is mainly focused on the scene understanding aspect (e.g., object recognition and obstacle detection) of assistive solutions. It provides guidance for researchers in this field to understand the advances during the last four and a half years. This is because deep learning techniques together with computer vision have become more powerful and accurate than ever in tasks like object detection. These advancements can bring a radical change in the development of high-quality assistive technologies for VI/blind users. Additionally, an overview of the current challenges and a comparison between different solutions is provided to indicate the pros and cons of existing approaches.

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Visually Impaired Job Alert Provider App

2023

2023 International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication

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Android Application for Object Recognition Using Neural Networks for the Visually Impaired

Cited by 5 publications

References 0 publications

Obstacle Detection and Distance Estimation for Visually Impaired People

Obstacle Detection and Distance Estimation for Visually Impaired People

Recent trends in computer vision-driven scene understanding for VI/blind users: a systematic mapping

Visually Impaired Job Alert Provider App

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