2024
DOI: 10.18280/mmep.110511
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Detecting Hidden Data in Images Using Convolutional Neural Networks

Erick Delenia,
Yoggy Harisusilo Putra,
Bayu Aditya Triwibowo
et al.

Abstract: Recent advancements in Deep Learning (DL) have driven the development of innovative methodologies, particularly within the domain of steganalysis for spatial domain images. Steganalysis, as the counterpart to steganography, is dedicated to uncovering concealed data within the content, making a digital image. Convolutional Neural Networks (CNNs), grounded in DL principles, have been influential in pushing the boundaries of this field. Despite the development of various CNN architectures that have raised the pre… Show more

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Cited by 2 publications
(1 citation statement)
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“…The CNN method outperforms in image recognition by replicating the image identification system of the human visual cortex, allowing for efficient processing of image information [10]. The CNN method has been extensively researched by scholars for the classification of plants in high-resolution images [11].…”
Section: Previous Researchmentioning
confidence: 99%
“…The CNN method outperforms in image recognition by replicating the image identification system of the human visual cortex, allowing for efficient processing of image information [10]. The CNN method has been extensively researched by scholars for the classification of plants in high-resolution images [11].…”
Section: Previous Researchmentioning
confidence: 99%