The proposed system incorporates a well designed pre-processing step before feeding the image data to CNN to capture essential characteristics of compression ...
Dec 6, 2017 · This paper aims to address the problem of classifying images based on the number of JPEG compressions they have undergone, by utilizing deep convolutional ...
Dec 6, 2017 · This paper aims to address the problem of classifying images based on the number of JPEG compressions they have undergone, by utilizing deep ...
Results on the standard UCID dataset demonstrate that the proposed system outperforms existing systems for multiple JPEG compression detection and is capable of ...
Jan 26, 2021 · In this article, I will give some details about the method we presented in the paper, then talk a little about the latest advances in DCT domain deep learning.
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Abstract. The authenticity of an evidence is a necessary and crucial re- quirement in forensic investigations and trials, expecially when it comes.
In this paper, we present a data-driven approach by using a convolutional neural network (CNN) which takes input from both raw JPEG DCT coefficients and ...
This paper presents a CNN solution by using raw DCT (discrete cosine transformation) coefficients from JPEG images as input, designed to reveal whether a JPEG ...
Convolutional neural networks (CNN) are a boon to image classification algorithms as it can learn highly abstract features and work with less parameter.
Oct 10, 2016 · This paper proposes a double JPEG compression detection algorithm based on a convolutional neural network (CNN).