Multi-task Learning Model for Detecting and Filtering Internet Violent Images for Children

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  • Kim Hoang Trung Le
  • Van Thanh Vinh Nguyen
  • Le Viet Hung Phan
  • Huu Nhat Minh Nguyen
Keywords: Multi-task learning, Violence detection, Web extension

Abstract

The Internet has emerged as an essential daily information access, but exposing children to inappropriate content can impair their early development. Existing content filtering methods exhibit limitations in accurately and efficiently detecting diverse inappropriate internet content. In this paper, we propose a multi-task learning model for detecting and filtering violent images to provide safer online experiences. The multi-task model is developed from the pre-trained lightweight base model such as MobileNetv2 to enable proper integration within web browser extensions. Pure training to detect violent images could raise false alarms in the classification results when the landscape or object images don’t contain any human, hence we develop two joint learning tasks such as detecting humans and detecting violent images simultaneously. Our experiments demonstrate that the proposed multi-task approach with binary rule achieves 98.5% accuracy, outperforming the single-task model for detecting violent images by a margin. Thereafter, the multi-task model is also integrated into the web extension to detect and filter out violent images to prevent children from harmful content.

Author Biographies

Kim Hoang Trung Le

Le Kim Hoang Trung1, Nguyen Van Thanh Vinh1, Phan Le Viet Hung1, and
Nguyen Huu Nhat Minh1
The University of Danang, Vietnam - Korea University of Information and
Communication Technology
trunglkh.21it@vku.udn.vn, vinhnvt.21it@vku.udn.vn,
hungplv.21ad@vku.udn.vn, nhnmminh@vku.udn.vn

Van Thanh Vinh Nguyen

Nguyen Van Thanh Vinh is pursuing the
B.Eng. degree in Information Technology
from the University of Danang, Vietnam -
Korea University of Information and Communication Technology. His research interests include software development, machine
learning and deep learning.
Email: vinhnvt.21it@vku.udn.vn

Le Viet Hung Phan

Phan Le Viet Hung is pursuing the B.Eng.
degree in Information Technology from
the University of Danang, Vietnam - Korea University of Information and Communication Technology. His research interests include software development, machine
learning and deep learning.
Email: hungplv.21ad@vku.udn.vn

Huu Nhat Minh Nguyen

Nguyen Huu Nhat Minh (M’20) received
Ph.D. degree in Computer Science and
Engineering from Kyung Hee University,
South Korea, in 2020. He continued PostDoc with Federated Learning and Democratized Learning at Intelligent Networking
lab, Kyung Hee University, South Korea.
He is Deputy Head of Department of Science, Technology, and International Cooperation, and In charge
of Research Program at Digital Science and Technology Institute,
The University of Danang – Vietnam - Korea University of Information and Communication Technology, Vietnam. His research
interests include wireless communications, federated learning,
NLP, and computer vision.
Email: nhnminh@vku.udn.vn

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Published
2024-05-26