Weapon detection and classification using CNN
| dc.contributor.author | Athavani, Shahin | |
| dc.contributor.author | Chaudhary, Mohammed Abid (18ET28) | |
| dc.contributor.author | Sayed, Abu Sufiyan (18ET34) | |
| dc.contributor.author | Shaikh, Mohd Danish (18ET43) | |
| dc.date.accessioned | 2022-06-17T10:28:49Z | |
| dc.date.available | 2022-06-17T10:28:49Z | |
| dc.date.issued | 2022-05 | |
| dc.description.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. | en_US |
| dc.identifier.uri | http://localhost:8080/xmlui/handle/123456789/3885 | |
| dc.language.iso | en | en_US |
| dc.publisher | AIKTC | en_US |
| dc.subject | Project Report - EXTC | en_US |
| dc.title | Weapon detection and classification using CNN | en_US |
| dc.type | Project Report | en_US |