Real Time Object Recognition and Classification using Deep Learning

Authors

  • Kiruthiga N  Department of Computer science and Engineering, Sri Krishna College of Technology, Coimbatore, Tamil Nadu, India
  • Divya E  Department of Computer science and Engineering, Sri Krishna College of Technology, Coimbatore, Tamil Nadu, India
  • Haripriya R  Department of Computer science and Engineering, Sri Krishna College of Technology, Coimbatore, Tamil Nadu, India
  • Haripriya V.  Department of Computer science and Engineering, Sri Krishna College of Technology, Coimbatore, Tamil Nadu, India

DOI:

https://doi.org//10.32628/CSEIT195262

Keywords:

Object Detection , Image Processing , Speech recognition , Deep learning, Convolutional neural networks, Background Subtraction.

Abstract

Navigation in indoor environments is highly challenging for visually impaired person, particularly in spaces visited for the first time. Various solutions have been proposed to deal with this challenge. In this project consider as the real time object Recognition and classification using deep learning algorithms. Object detection mainly deals with identification of real time objects such as people, animals, and objects. Object detection algorithm uses a wide range of image processing applications for extracting the object's desired portion. This enables one to identify the objects and calculate the accuracy of the object and deliver through voice. Using this information, the system determines the user's trajectory and can locate possible obstacles in that route.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2019-04-30

Issue

Volume 5, Issue 2, March-April-2019

Section

Research Articles

License

Copyright (c) IJSRCSEIT

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Kiruthiga N, Divya E, Haripriya R, Haripriya V., " Real Time Object Recognition and Classification using Deep Learning, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 5, Issue 2, pp.355-359, March-April-2019. Available at doi : https://doi.org/10.32628/CSEIT195262