Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/3885
Title: Weapon detection and classification using CNN
Authors: Athavani, Shahin
Chaudhary, Mohammed Abid (18ET28)
Sayed, Abu Sufiyan (18ET34)
Shaikh, Mohd Danish (18ET43)
Keywords: Project Report - EXTC
Issue Date: May-2022
Publisher: AIKTC
Abstract: Gun violence in a lot of areas remains stubbornly high. Therefore, limiting gun violence has been a priority in recent years. In this presentation, we will be implementing the use of Deep learning algorithms to detect any firearms / weapons in real time, to improve response times and reduce potential harm. The increase of video surveillance in public spaces, and the proliferation of body cameras for police can potentially be leveraged for gun detection systems. Video systems could alert police and surveillance personnel when a gun is detected in real time, resulting in prompter action. The proposed system in this presentation is a weapon detection system that makes use of TensorFlow object detection API. The project will involve the use of various resources for implementation, such as: Python, TensorFlow object detection API, OpenCV, Google Collab, NumPy etc.
URI: http://localhost:8080/xmlui/handle/123456789/3885
Appears in Collections:EXTC Engineering - Project Reports

Files in This Item:
File Description SizeFormat 
18ET28.pdf
  Until 2025-06-30
Black Book4.06 MBAdobe PDFView/Open Request a copy


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.