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Librería: Books Puddle, New York, NY, Estados Unidos de America
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Publicado por Biblioscholar 11/19/2012, 2012
ISBN 10: 1288311931 ISBN 13: 9781288311934
Idioma: Inglés
Librería: BargainBookStores, Grand Rapids, MI, Estados Unidos de America
EUR 52,89
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Añadir al carritoPaperback or Softback. Condición: New. Multi-Class Classification for Identifying JPEG Steganography Embedding Methods. Book.
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Librería: CitiRetail, Stevenage, Reino Unido
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Añadir al carritoPaperback. Condición: new. Paperback. Over 725 steganography tools are available over the Internet, each providing a method for covert transmission of secret messages. This research presents four steganalysis advancements that result in an algorithm that identifies the steganalysis tool used to embed a secret message in a JPEG image file. The algorithm includes feature generation, feature preprocessing, multi-class classification and classifier fusion. The first contribution is a new feature generation method which is based on the decomposition of discrete cosine transform (DCT) coefficients used in the JPEG image encoder. The generated features are better suited to identifying discrepancies in each area of the decomposed DCT coefficients. Second, the classification accuracy is further improved with the development of a feature ranking technique in the preprocessing stage for the kernel Fisher's discriminant (KFD) and support vector machines (SVM) classifiers in the kernel space during the training process. Third, for the KFD and SVM two-class classifiers a classification tree is designed from the kernel space to provide a multi-class classification solution for both methods. Fourth, by analyzing a set of classifiers, signature detectors, and multi-class classification methods a classifier fusion system is developed to increase the detection accuracy of identifying the embedding method used in generating the steganography images.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
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Publicado por BiblioScholar 2012-11-19, 2012
ISBN 10: 1288311931 ISBN 13: 9781288311934
Idioma: Inglés
Librería: Chiron Media, Wallingford, Reino Unido
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Librería: Chiron Media, Wallingford, Reino Unido
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
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Librería: Revaluation Books, Exeter, Reino Unido
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Añadir al carritoPaperback. Condición: Brand New. 194 pages. 7.44x0.41x9.69 inches. In Stock.
Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
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Librería: THE SAINT BOOKSTORE, Southport, Reino Unido
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Añadir al carritoPaperback / softback. Condición: New. New copy - Usually dispatched within 3 working days. 384.
Librería: CitiRetail, Stevenage, Reino Unido
EUR 34,84
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Añadir al carritoHardcover. Condición: new. Hardcover. Over 725 steganography tools are available over the Internet, each providing a method for covert transmission of secret messages. This research presents four steganalysis advancements that result in an algorithm that identifies the steganalysis tool used to embed a secret message in a JPEG image file. The algorithm includes feature generation, feature preprocessing, multi-class classification and classifier fusion. The first contribution is a new feature generation method which is based on the decomposition of discrete cosine transform (DCT) coefficients used in the JPEG image encoder. The generated features are better suited to identifying discrepancies in each area of the decomposed DCT coefficients. Second, the classification accuracy is further improved with the development of a feature ranking technique in the preprocessing stage for the kernel Fisher's discriminant (KFD) and support vector machines (SVM) classifiers in the kernel space during the training process. Third, for the KFD and SVM two-class classifiers a classification tree is designed from the kernel space to provide a multi-class classification solution for both methods. Fourth, by analyzing a set of classifiers, signature detectors, and multi-class classification methods a classifier fusion system is developed to increase the detection accuracy of identifying the embedding method used in generating the steganography images.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Librería: Kennys Bookstore, Olney, MD, Estados Unidos de America
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Añadir al carritoCondición: New. 2012. paperback. . . . . . Books ship from the US and Ireland.
Publicado por Creative Media Partners, LLC Mai 2025, 2025
ISBN 10: 1025122763 ISBN 13: 9781025122762
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 27,52
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Añadir al carritoTaschenbuch. Condición: Neu. Neuware - Over 725 steganography tools are available over the Internet, each providing a method for covert transmission of secret messages. This research presents four steganalysis advancements that result in an algorithm that identifies the steganalysis tool used to embed a secret message in a JPEG image file. The algorithm includes feature generation, feature preprocessing, multi-class classification and classifier fusion. The first contribution is a new feature generation method which is based on the decomposition of discrete cosine transform (DCT) coefficients used in the JPEG image encoder. The generated features are better suited to identifying discrepancies in each area of the decomposed DCT coefficients. Second, the classification accuracy is further improved with the development of a feature ranking technique in the preprocessing stage for the kernel Fisher's discriminant (KFD) and support vector machines (SVM) classifiers in the kernel space during the training process. Third, for the KFD and SVM two-class classifiers a classification tree is designed from the kernel space to provide a multi-class classification solution for both methods. Fourth, by analyzing a set of classifiers, signature detectors, and multi-class classification methods a classifier fusion system is developed to increase the detection accuracy of identifying the embedding method used in generating the steganography images.
Publicado por Creative Media Partners, LLC, 2025
ISBN 10: 1025122763 ISBN 13: 9781025122762
Idioma: Inglés
Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de America
EUR 22,88
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Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Librería: moluna, Greven, Alemania
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Añadir al carritoCondición: New. KlappentextrnrnOver 725 steganography tools are available over the Internet, each providing a method for covert transmission of secret messages. This research presents four steganalysis advancements that result in an algorithm that identifies th.
Publicado por Creative Media Partners, LLC Mai 2025, 2025
ISBN 10: 1025119789 ISBN 13: 9781025119786
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 44,53
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Añadir al carritoBuch. Condición: Neu. Neuware.
Publicado por Creative Media Partners, LLC Nov 2012, 2012
ISBN 10: 1288311931 ISBN 13: 9781288311934
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 58,13
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Añadir al carritoTaschenbuch. Condición: Neu. Neuware - Over 725 steganography tools are available over the Internet, each providing a method for covert transmission of secret messages. This research presents four steganalysis advancements that result in an algorithm that identifies the steganalysis tool used to embed a secret message in a JPEG image file. The algorithm includes feature generation, feature preprocessing, multi-class classification and classifier fusion. The first contribution is a new feature generation method which is based on the decomposition of discrete cosine transform (DCT) coefficients used in the JPEG image encoder. The generated features are better suited to identifying discrepancies in each area of the decomposed DCT coefficients. Second, the classification accuracy is further improved with the development of a feature ranking technique in the preprocessing stage for the kernel Fisher's discriminant (KFD) and support vector machines (SVM) classifiers in the kernel space during the training process. Third, for the KFD and SVM two-class classifiers a classification tree is designed from the kernel space to provide a multi-class classification solution for both methods. Fourth, by analyzing a set of classifiers, signature detectors, and multi-class classification methods a classifier fusion system is developed to increase the detection accuracy of identifying the embedding method used in generating the steganography images.