中圖分類號(hào)： TN91
文獻(xiàn)標(biāo)識(shí)碼： A
DOI：10.16157/j.issn.0258-7998.211757
中文引用格式： 張聰，張恒，張立坤，等. 基于深度殘差神經(jīng)網(wǎng)絡(luò)的博彩網(wǎng)頁(yè)識(shí)別算法設(shè)計(jì)[J].電子技術(shù)應(yīng)用，2022，48(2)：15-18.
英文引用格式： Zhang Cong，Zhang Heng，Zhang Likun，et al. Gambling web page recognition algorithm design based on deep residual neural network[J]. Application of Electronic Technique，2022，48(2)：15-18.

Gambling web page recognition algorithm design based on deep residual neural network

Abstract： The Internet has an important impact on people′s life and work. However, there are a large number of harmful gambling websites hidden in cyberspace, which is easy to cause losses and troubles to netizens, it can even disturb society order. Therefore, it is of great significance to study the efficient recognition method of such websites. In this paper, the deep residual neural network is used to solve the problem of gambling web page recognition, and the algorithm GamblingRec is designed based on principle of deep residual network. The results show that the accuracy of GamblingRec reaches 95.16%, and the positive sample recall rate is 93.21%，which indicates that the method based on deep residual neural network can be applied for gambling web page recognition, and can achieve high recognition performance.

Key words : convolutional neural network；residual network；gambling；web page classification；ResNet