Novel Deep Learning Pipeline for Automatic Weapon Detection

• URL: http://arxiv.org/abs/2309.16654v1
• Date: Thu, 28 Sep 2023 17:55:14 GMT
• Title: Novel Deep Learning Pipeline for Automatic Weapon Detection
• Authors: Haribharathi Sivakumar and Vijay Arvind.R and Pawan Ragavendhar V and G.Balamurugan
• Abstract summary: Weapon and gun violence have recently become a pressing issue. Real-time surveillance video is captured and recorded in almost all public forums and places. This paper proposes a novel pipeline consisting of an ensemble of convolutional neural networks with distinct architectures.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Weapon and gun violence have recently become a pressing issue today. The degree of these crimes and activities has risen to the point of being termed as an epidemic. This prevalent misuse of weapons calls for an automatic system that detects weapons in real-time. Real-time surveillance video is captured and recorded in almost all public forums and places. These videos contain abundant raw data which can be extracted and processed into meaningful information. This paper proposes a novel pipeline consisting of an ensemble of convolutional neural networks with distinct architectures. Each neural network is trained with a unique mini-batch with little to no overlap in the training samples. This paper will present several promising results using multiple datasets associated with comparing the proposed architecture and state-of-the-art (SoA) models. The proposed pipeline produced an average increase of 5% in accuracy, specificity, and recall compared to the SoA systems.

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