Modeling Objects with Artificial Intelligence Based Image Processing Techniques: Object Detection with Mask R-CNN

Year 2025, Volume: 13 Issue: 1, 17 - 21, 31.01.2025

Ömer Faruk Ereken , Çiğdem Tarhan

https://doi.org/10.21541/apjess.1542885

Abstract

Object detection and classification on digital images have great importance in the digitalizing world. After deep learning methods started being implemented for object detection, classification and segmentation a rapid development has been monitored in the field. One of the most successful methods in the field is Mask R-CNN. It can be used in order to detect and segment purposes for many different objects. This study contains the use of Mask R-CNN for weapon detection, specifically handguns. Nowadays, there are many cameras in public areas and these cameras can detect weapons before a forensic incident. Our model achieved a mean average precision (mAP) of 0.78 in the detection of handguns on test data. Our findings verify the potential of deep learning in security by detecting threats in images and live videos.

Keywords

Object Detection, Handgun Detection, Mask R-CNN, Instance Segmentation, Deep Learning

Ethical Statement

This article is an extended version of an unpublished paper titled 'Modeling Objects With Artificial Intelligence Based Image Processing Techniques: Handgun Detection With MASK R-CNN' presented at the 10th International Conference on Management Information Systems on 18-20 October 2023.

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