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Micro-Electronics and Telecommunication Engineering pp 601–610Cite as

Improving the Performance of Video Content Genuineness Using Convolution Neural Network

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Part of the Lecture Notes in Networks and Systems book series (LNNS,volume 106)

Abstract

Video searching in search engines uses metadata information to find the relevant videos according to the search queries. Metadata information mainly comprises the title and description of the video. The major drawback of this approach is that it overlooks whether or not the content of the video is genuine or not. Since the metadata information is provided by the uploader, the person may provide false information about it. Therefore, there is a need of improving the results of video searched. The proposed work classifies the video in different categories and then compares the tag provided to each video with the tags that were extracted from the metadata of the video. The other factor like views count, likes and dislikes, comments is also considered for the ranking of the video searched. It improves the genuineness of the content of the video searched.

Keywords

  • Convolution neural network
  • Deep neural network
  • Image classification
  • Video classification

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  • DOI: 10.1007/978-981-15-2329-8_61
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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Jaypee Institute of Information Technology, Noida, India

    Bharat Gupta, Vasvi Bajaj & Rajat Bhusan Panda

  2. Faculty of Information & Communication Technology, University of Malta, Msida, Malta

    Lalit Garg

Authors
  1. Bharat Gupta
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  2. Vasvi Bajaj
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  3. Rajat Bhusan Panda
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  4. Lalit Garg
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Corresponding author

Correspondence to Bharat Gupta .

Editor information

Editors and Affiliations

  1. Department of Electronics and Communication Engineering, SRM Institute of Science and Technology, Delhi NCR Campus, Ghaziabad, India

    Dr. Devendra Kumar Sharma

  2. Department of Automatics and Applied Software, “Aurel Vlaicu” University of Arad, Arad, Romania

    Prof. Valentina Emilia Balas

  3. Department of Multimedia and Virtual Reality, Institute of Information Technology, Vietnam National University, Hanoi, Vietnam

    Prof. Dr. Le Hoang Son

  4. Department of Electronics and Communication Engineering, SRM Institute of Science and Technology, Delhi NCR Campus, Ghaziabad, India

    Dr. Rohit Sharma

  5. Department of Electrical and Electronics Engineering, Trakya University, Edirne, Turkey

    Dr. Korhan Cengiz

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Gupta, B., Bajaj, V., Panda, R.B., Garg, L. (2020). Improving the Performance of Video Content Genuineness Using Convolution Neural Network. In: Sharma, D.K., Balas, V.E., Son, L.H., Sharma, R., Cengiz, K. (eds) Micro-Electronics and Telecommunication Engineering. Lecture Notes in Networks and Systems, vol 106. Springer, Singapore. https://doi.org/10.1007/978-981-15-2329-8_61

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  • DOI: https://doi.org/10.1007/978-981-15-2329-8_61

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-2328-1

  • Online ISBN: 978-981-15-2329-8

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