论文标题
从错误级别分析和卷积神经网络中检测基于工具的编辑图像
Detection of Tool based Edited Images from Error Level Analysis and Convolutional Neural Network
论文作者
论文摘要
图像伪造是图像取证的问题，可以使用深度学习来利用其检测。在本文中，我们提出了一种使用具有错误级别分析和卷积神经网络的图像编辑工具进行的真实和篡改图像的方法。该过程是在CASIA ITDE V2数据集上执行的，分别对50个时代和100个时代进行了训练。使用图表表示训练和验证集的各个精度。
Image Forgery is a problem of image forensics and its detection can be leveraged using Deep Learning. In this paper we present an approach for identification of authentic and tampered images done using image editing tools with Error Level Analysis and Convolutional Neural Network. The process is performed on CASIA ITDE v2 dataset and trained for 50 and 100 epochs respectively. The respective accuracies of the training and validation sets are represented using graphs.
