Detection of Human Behaviour by Object Recognition using Deep Learning: A Review

Abstract

The major drawback of the society is the falsehood of human nature; so prediction of nature of the individual by analysing the video or image of that person is highly necessary. From the post World War II period due to the advancement of technology since the past few decades many countries have developed low cost cameras with high resolution. They generally use the RGB and depth features to enhance the image quality captured by the camera. Hence object recognition is the new branch of computer science which emerges. It has got a close relationship with image understanding and analysis of video; which encourages several researchers to work in this domain since past few years. As the branch of deep learning develops handful of efficient tools have been develop which prove to be highly efficient to learn high level deeper features of the image and semantics. In this paper a review on object recognition using deep learning has been discussed. This paper includes basics of deep learning and object recognition. Then we have discussed some tools required to perform object recognition as well as moving object recognition and finally some future goals of this subject have been discussed.

Authors and Affiliations

Mr. Utsab Mukherjee, Prof. Samir Kumar Bandyopadhyay

Keywords

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  • EP ID EP747845
  • DOI 10.21276/ijircst.2020.8.2.2
  • Views 55
  • Downloads 0

How To Cite

Mr. Utsab Mukherjee, Prof. Samir Kumar Bandyopadhyay (2020). Detection of Human Behaviour by Object Recognition using Deep Learning: A Review. International Journal of Innovative Research in Computer Science and Technology, 8(2), -. https://europub.co.uk/articles/-A-747845