Detection of Violent Elements in Digital Games Using Deep Learning

被引：0
作者：
Yalçın N. [1 ]
Çapanoğlu A.E. [2 ]
机构：
[1] Department of Computer and Instructional Technologies Education, Gazi University, Ankara
[2] Faculty of Engineering, Gazi University, Ankara
来源：
SN Computer Science | / 4卷 / 5期
关键词：
CNN; Deep learning; Violation in digital games; YOLOv4; Tiny;
D O I：
10.1007/s42979-023-02064-w
中图分类号：
学科分类号：
摘要：
Detection of violence in digital games can be achieved by detecting elements of violence in digital game frames. For young, the detection of these elements can play an important role in the detection and prevention of violence by taking early actions. Violence detection from within the image is based on the analysis of images in periods. This means a large amount of computation based on image processing. In this study, an image detection algorithms based on CNN models are proposed using YOLOV4 Tiny advanced object detection algorithms. It has been shown that the proposed method can be used for real time games with detection speed and 93% accuracy performance. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.
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