01644nam0 2200325 i 450 SUN005934020151120101600.498978-35-403-9942-10.0020070518d2007 |0engc50 baengDE|||| |||||Stable approximate evaluation of unbounded operatorsCharles W. GroetschBerlin : Springer2007X127 p. ; 24 cmPubblicazione disponibile anche in formato elettronico.001SUN01022502001 *Lecture notes in mathematics1894210 Berlin [etc.]Springer1964-215 Dal 2011 i volumi sono disponibili in formato elettronico.47A52Linear operators and ill-posed problems, regularization [MSC 2020]MFSUNC02079047A58Linear operator approximation theory [MSC 2020]MFSUNC02079165J20Numerical solutions of ill-posed problems in abstract spaces; regularization [MSC 2020]MFSUNC02524465J22Numerical solution to inverse problems in abstract spaces [MSC 2020]MFSUNC029362BerlinSUNL000066Groetsch, Charles W.SUNV04070527779SpringerSUNV000178650ITSOL20201026RICAhttp://link.springer.com/book/10.1007/3-540-39942-9ContentsSUN0059340UFFICIO DI BIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICA08PREST 47-XX 1709 08 7697 I 20070518 Stable approximate evaluation of unbounded operators230552UNICAMPANIA04373nam 2200757 450 991013761270332120230125234627.01-283-60392-697866139163721-118-43798-51-118-43796-91-118-43795-010.1002/9781118437957(CKB)3190000000032947(EBL)1022347(SSID)ssj0000711543(PQKBManifestationID)11416643(PQKBTitleCode)TC0000711543(PQKBWorkID)10722516(PQKB)11028464(DLC) 2012024649(CaBNVSL)mat06331046(IDAMS)0b0000648193ddab(IEEE)6331046(Au-PeEL)EBL1022347(CaPaEBR)ebr10602086(CaONFJC)MIL391637(OCoLC)809555684(CaSebORM)9781118437988(MiAaPQ)EBC1022347(PPN)244333815(EXLCZ)99319000000003294720151222d2012 uy engurunu|||||txtccrMachine learning in image steganalysis /Hans Georg Schaathun1st editionChichester, West Sussex, U.K. :John Wiley,2012.[Piscataqay, New Jersey] :IEEE Xplore,[2012]1 online resource (394 p.)Wiley - IEEEDescription based upon print version of record.0-470-66305-7 Includes bibliographical references and index.Front Matter -- Overview. Introduction -- Steganography and Steganalysis -- Getting Started with a Classifier -- Features. Histogram Analysis -- Bit-Plane Analysis -- More Spatial Domain Features -- The Wavelets Domain -- Steganalysis in the JPEG Domain -- Calibration Techniques -- Classifiers. Simulation and Evaluation -- Support Vector Machines -- Other Classification Algorithms -- Feature Selection and Evaluation -- The Steganalysis Problem -- Future of the Field -- Bibliography -- Index.Steganography is the art of communicating a secret message, hiding the very existence of a secret message. This is typically done by hiding the message within a non-sensitive document. Steganalysis is the art and science of detecting such hidden messages. The task in steganalysis is to take an object (communication) and classify it as either a steganogram or a clean document. Most recent solutions apply classification algorithms from machine learning and pattern recognition, which tackle problems too complex for analytical solution by teaching computers to learn from empirical data. Part 1of the book is an introduction to steganalysis as part of the wider trend of multimedia forensics, as well as a practical tutorial on machine learning in this context. Part 2 is a survey of a wide range of feature vectors proposed for steganalysis with performance tests and comparisons. Part 3 is an in-depth study of machine learning techniques and classifier algorithms, and presents a critical assessment of the experimental methodology and applications in steganalysis.Key features: . Serves as a tutorial on the topic of steganalysis with brief introductions to much of the basic theory provided, and also presents a survey of the latest research.. Develops and formalises the application of machine learning in steganalysis; with much of the understanding of machine learning to be gained from this book adaptable for future study of machine learning in other applications. . Contains Python programs and algorithms to allow the reader to modify and reproduce outcomes discussed in the book.. Includes companion software available from the author's website.Wiley - IEEEMachine learningWavelets (Mathematics)Data encryption (Computer science)Machine learning.Wavelets (Mathematics)Data encryption (Computer science)006.3/1SCI067000bisacshSchaathun Hans Georg845658CaBNVSLCaBNVSLCaBNVSLBOOK9910137612703321Machine learning in image steganalysis1887878UNINA