Editor/Reviewer loginFrequency : 12 issues per year
Subject : Computer Applications and Technology
ISSN : 2319–8656 (Online)
IJCATR Volume 12 Issue 3
A Two-stream Convolutional Neural Network-based Pornography Recognition Method
Congcong He, Qinglin Huang, Jieyuan Luo
10.7753/IJCATR1203.1004
keywords : Video Identification, Two-stream convolutional neural network, Keyframe styling
The main approach taken to identify pornographic video content is achieved by performing pornography detection on the video content. By extracting features from video key frames and using some common neural network models to recognize the extracted key frame images, a certain accuracy rate can be obtained. However, another key information of video recognition, action information, is ignored, which leads to misclassification of some indistinguishable videos such as sumo wrestling and boxing. A dual-stream convolutional neural network-based pornographic video recognition method is proposed to address this problem. The experimental results show that the dual-stream convolutional neural network effectively improves the recognition rate of indistinguishable pornographic videos.
@artical{c1232023ijcatr12031004,
Title = "A Two-stream Convolutional Neural Network-based Pornography Recognition Method ",
Journal ="International Journal of Computer Applications Technology and Research(IJCATR)",
Volume = "12",
Issue ="3",
Pages ="14 - 17",
Year = "2023",
Authors ="Congcong He, Qinglin Huang, Jieyuan Luo"}
Propose a video segmentation method.
Proposed optical flow map extraction method.
Proposed a two-stream convolutional convolutional network for pornography recognition.
Proposed a method to extract keyframes.