instantaneous object identification and intimation framework for typhlotic people
AARTHY.M,KEERTHANA.S ,A.SUNITHA,M.E
Published in International Journal of Advanced Research in Computer Science Engineering and Information Technology
ISSN: 2321-3337 Impact Factor:1.521 Volume:6 Issue:3 Year: 02 April,2021 Pages:1519-1524
Abstract
Blind people face several problems in their life, one of these problems that is the most important one is detection the obstacles when they are walking. Our research is on obstacle detection in order to reduce navigation difficulties for visually impaired people. Moving through an unknown environment becomes a real challenge when we can’t rely on our own eyes. To help the blind people the visual world has to be transformed into the audio world with the potential to inform them about objects. In this paper algorithm for real time detection and tracking of object is proposed by deep learning. Object recognition is one of the major applications in deep learning. It can be done by many ways, like by using pre-trained model using CNN(Convolution Neural Network), transfer learning or from the scratch by feeding n number of datasets to recognize the object with more number of epochs to increase the accuracy of the result. The model is trained with more than lakhs of images to recognize the object.
Kewords
TYPHLOTIC,CNN
Reference
[1]: Obinna Ethelbert, Faraz Fatemi Moghaddam, Philipp Wieder, Ramin Yahyapour, “A JSON Token-Based Authentication and Access Management Schema for Cloud SaaS Applications”, 2017 IEEE 5th International Conference on Future Internet of Things and Cloud, pp 1-7, 2017. [2]: Salman Ahmed, Qamar Mahmood, “An authentication-based scheme for applications using JSON web token”, 978-1-7281-4001-8/19/$31.00 ©2019 IEEE, pp 1-4, 2019. [3]: Muhamad Haekal, Eliyani, “Token- Based Authentication Using JSON Web Token on SIKASIR RESTful Web Service”, 2016 International Conference on Informatics and Computing (ICIC), pp 1-5, 2016. [4]: Iman M. Almomani, Nour Y. Alkhalil, Enas M. Ahmad, Rania M. Jodeh, “Ubiquitous GPS Vehicle Tracking and Management System”, 2011 IEEE Journal Conference on Applied Electrical Engineering and Computing Technologies (AEECT), pp 1-6, 2011.
