隐写分析技术
联营
卷积神经网络
模式识别(心理学)
人工智能
隐写术
计算机科学
特征(语言学)
激活函数
特征提取
图像(数学)
人工神经网络
语言学
哲学
作者
Qun Wang,Minqing Zhang,Fuqiang Di,Xueni Jiang
标识
DOI:10.1109/isrimt53730.2021.9596658
摘要
With the continuous development of Steganalysis based on convolutional neural network, in order to obtain higher steganalysis accuracy, softpooling method is used to replace the original conventional pooling, which not only retains the advantages of conventional pooling in reducing the amount of calculation and compressing the size of feature map, but also prevents the loss of steganographic feature information. The Relu activation function is replaced by the Mish activation function. The accuracy of steganalysis is improved. The experimental results show that the accuracy of Xu and SRNET is improved by 0.53% and 1.27% respectively.
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