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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14

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Paper Title: Suspecting Abnormal Activities Under Survilleance
Authors Name: Thudi Arshith Reddy , Alugubelly Varun Reddy , Dr Reddy Saisindhutheja , Yarlagadda Pavan
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IJRTI_185460
Published Paper Id: IJRTI2303075
Published In: Volume 8 Issue 3, March-2023
DOI:
Abstract: The global crime rate has been increasing in terms of numbers, with an estimated hundred million offences committed each year. Surveillance cameras have been installed at every street corner to capture and record such activities. Detecting such acts in time might reduce a person’s potential danger. It is difficult for human supervision of such systems to discover such behaviours on the spot for every surveillance CCTV video. In order to discover such actions as soon as possible, this study proposes an intelligence surveillance system that recognises criminal scenes and shows crime activity for a recorded surveillance video using a deep learning approach. As a result, the suggested systems employ deep learning techniques CNN and LSTM to categorise and detect odd actions for recorded data.The Convolution neural network is used to learn and train the data.
Keywords: Suspicious Activity,CNN,Lstm,Recorded data
Cite Article: "Suspecting Abnormal Activities Under Survilleance", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 3, page no.437 - 441, March-2023, Available :http://www.ijrti.org/papers/IJRTI2303075.pdf
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ISSN: 2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publication Details: Published Paper ID: IJRTI2303075
Registration ID:185460
Published In: Volume 8 Issue 3, March-2023
DOI (Digital Object Identifier):
Page No: 437 - 441
Country: Hyderabad , Telangana , India
Research Area: Computer Science & Technology 
Publisher : IJ Publication
Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2303075
Published Paper PDF: https://www.ijrti.org/papers/IJRTI2303075
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED, Journal Starting Year (ESTD) : 2016

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