Multiple JPEG detection using convolutional neural networks in the DCT domain다중 JPEG 압축 탐지를 위한 컨볼루션 신경망 연구

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dc.contributor.advisorLee, Heungkyu-
dc.contributor.advisor이흥규-
dc.contributor.authorSon, Minseok-
dc.date.accessioned2023-06-26T19:31:40Z-
dc.date.available2023-06-26T19:31:40Z-
dc.date.issued2021-
dc.identifier.urihttp://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=1007056&flag=dissertationen_US
dc.identifier.urihttp://hdl.handle.net/10203/309569-
dc.description학위논문(석사) - 한국과학기술원 : 전산학부, 2021.2,[iv, 26 p. :]-
dc.description.abstractThe recent rapid growth of social network services (SNSs) has changed the way in which images are shared. Since images undergo JPEG encoding and decoding many times through the repeated uploads and downloads, multiple JPEG compression detection is becoming more critical in the digital image forensic field. Existing methods are based on the statistical characteristics of images and do not utilize recent advances in deep learning. Moreover, the traces of JPEG compression are small. The more compression occurs, the harder it is for the classifier to detect-
dc.description.abstractit is difficult to identify the number of compressions by adopting well-defined convolutional neural networks (CNNs) on computer vision field. In this paper, we propose a novel CNN for multiple JPEG compression detection on the 2D discrete cosine transform (DCT) histogram. The proposed method achieves higher performance than state-of-the-art works and shows considerable experimental results for a practical scenario using SNS platforms.-
dc.languageeng-
dc.publisher한국과학기술원-
dc.subjectImage forensic▼aMultiple JPEG compression detection▼a2D DCT histogram▼aConvolutional neural network-
dc.subject이미지 포렌식▼a다중 JPEG 압축 탐지▼a2차원 DCT 히스토그램▼a컨볼루션 신경망-
dc.titleMultiple JPEG detection using convolutional neural networks in the DCT domain-
dc.title.alternative다중 JPEG 압축 탐지를 위한 컨볼루션 신경망 연구-
dc.typeThesis(Master)-
dc.identifier.CNRN325007-
dc.description.department한국과학기술원 :전산학부,-
dc.contributor.alternativeauthor손민석-
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