handbook fingerprint recognition de maltoni davide (40 resultados)

Condición: Very Good. Used book that is in excellent condition. May show signs of wear or have minor defects.

Condición: Good. Good condition. DVD included. A copy that has been read but remains intact. May contain markings such as bookplates, stamps, limited notes and highlighting, or a few light stains.

Condición: Very Good. Ships from the UK. Former library book; may include library markings. Used book that is in excellent condition. May show signs of wear or have minor defects.

gebundene Ausgabe. Condición: Gut. 348 Seiten, CD Der Erhaltungszustand des hier angebotenen Werks ist trotz seiner Bibliotheksnutzung sehr sauber und kann entsprechende Merkmale aufweisen (Rückenschild, Instituts-Stempel.). In ENGLISCHER Sprache. Sprache: Englisch Gewicht in Gramm: 880.

Hardcover. Condición: Very Good. includes sealed CD-ROM; VERY GOOD hardcover, no marks in text, clean exterior. Book.

Hardcover. Condición: New.

Condición: Good. CD Missing. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.

23,5 x 18 cm. Condición: Gut. 2. Auflage, 2nd edition,. XVI, 494 Seiten Innen sauberer, guter Zustand. Mit vielen Abbildungen und 1 CD im hinteren Innendeckel. Hardcover, Pappeinband, mit den üblichen Bibliotheks-Markierungen, Stempeln und Einträgen, innen wie außen, siehe Bilder. Ecken berieben. Einbanddeckel berieben. B10-02-01F|A33 Sprache: Englisch Gewicht in Gramm: 1065.

Condición: Good. 2. ** CD is included **; Good; Hardcover; Covers are shelfworn and edgeworn; Unblemished textblock edges; Highlighting/notes to about 30 pages in the beginning of the book, while the remainder of the pages are unmarked; The binding is excellent with a straight spine; This book will be shipped in a sturdy cardboard box with foam padding; Medium Format (8.5" - 9.75" tall); Dark blue-green covers with title in white lettering; 2nd Edition; 2009, Springer-Verlag Publishing; 510 pages; "Handbook of Fingerprint Recognition," by Davide Maltoni, et al.

Condición: New.

Condición: New.

Condición: New. In.

Paperback. Condición: new. Paperback. A major new professional reference work on fingerprint security systems and technology from leading international researchers in the field. Handbook provides authoritative and comprehensive coverage of all major topics, concepts, and methods for fingerprint security systems. This unique reference work is an absolutely essential resource for all biometric security professionals, researchers, and systems administrators. This comprehensive handbook provides in-depth coverage of the most recent advances and practices in fingerprint recognition. Readers will find authoritative coverage of all the major concepts, topics, and security methods associated with the subject. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Hardcover. Condición: Very Good+ with no dust jacket. 348 pp, 178 illus. Spine bumped. Unread. Includes unopened CD-ROM. An in-depth reference on automatic fingerprint recognition. ; 8vo 8" - 9" tall.

Condición: As New. Unread book in perfect condition.

Condición: New.

Condición: new.

Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - With their distinctiveness and stability over time, fingerprints continue to be the most widely used anatomical characteristic in systems that automatically recognize a person's identity.This fully updated third edition provides in-depth coverage of the state-of-the-art in fingerprint recognition readers, feature extraction, and matching algorithms and applications. Deep learning (resurgence beginning around 2012) has been a game changer for artificial intelligence and, in particular, computer visionand biometrics. Performance improvements (both recognition accuracy and speed) for most biometric modalities can be attributed to the use of deep neural networks along with availability of large training sets and powerful hardware. Fingerprint recognition has also been approached by deep learning, resulting in effective and efficient methods for automated recognition and for learning robust fixed-length representations. However, the tiny ridge details in fingerprints known as minutiae are still competitive with the powerful representations learned by huge neural networks trained on big data.Features & Benefits:Reflects the progress made in automated techniques for fingerprint recognition over the past five decadesReviews the evolution of sensing technology: from bulky optical devices to in-display readers in smartphonesDedicates an entire new chapter to latent fingerprint recognition, which is nowadays feasible in 'lights-out' modeIntroduces classical and learning-based techniques for local orientation extraction, enhancement, and minutiae detectionProvides an updated review of presentation-attack-detection techniques and their performance evaluationDiscusses the evolution of minutiae matching from rich local descriptors to Minutiae Cylinder Code Presents the development of feature-based matching: from FingerCode to handcrafted textural features to deep featuresReviews fingerprint synthesis, including recent Generative Adversarial NetworksThe revised edition of this must-read reference, written by leading international researchers, covers all critical aspects of fingerprint security system design and technology. It is an essential resource for all security and biometrics professionals, researchers, practitioners, developers, and systems administrators, and can serve as an easy-to-read reference for an undergraduate or graduate course on biometrics. Davide Maltoni is full professor in the Department of Computer Science (DISI) at the University of Bologna, where he also co-directs the Biometrics Systems Laboratory (BioLab). Dario Maio is full professor in the DISI and a co-director of the BioLab. Anil K. Jain is university distinguished professor in the Department of Computer Science and Engineering at Michigan State University. Jianjiang Feng is associate professor in the Department of Automation at Tsinghua University.

Taschenbuch. Condición: Neu. Neuware -A major new professional reference work on fingerprint security systems and technology from leading international researchers in the field. Handbook provides authoritative and comprehensive coverage of all major topics, concepts, and methods for fingerprint security systems. This unique reference work is an absolutely essential resource for all biometric security professionals, researchers, and systems administrators.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 512 pp. Englisch.

Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - With their proven distinctiveness and stability over time, fingerprints continue to be the most widely used anatomical characteristic in systems that automatically recognize a person's identity.This markedly enhanced second edition provides in-depth coverage of the recent advances and practices in fingerprint recognition. Readers will find comprehensive and authoritative coverage of all the major concepts, topics, and systems and security issues associated with fingerprint recognition systems. Written with the same formula that made the success of the first edition, this unique professional reference includes state-of-the-art techniques in fingerprint matching, and covers developments in sensor technology, performance evaluation, international standards, and system security. Features & Benefits:\* Covers the latest research in fingerprint recognition algorithms and techniques \* Reviews recent guidelines for scanner quality evaluation and certification, and provides examples of new fingerprint sensors \* Provides introductory material on all components and modules of a fingerprint recognition system\* Covers evaluations of fingerprint recognition algorithms and interoperability, including: FpVTE, MINEX, FVC2004 and FVC2006 \* Integrates numerous supporting graphs, tables, charts, and performance data \*Examines the design of secure fingerprint systems \* Supplies an extensive annotated bibliography of citations and literature sources.\* Contains helpful chapter overviews and summaries and consistent notation, for ease of use and accessibilityThe revised edition of this indispensible reference, written by leading international researchers, covers all critical aspects of fingerprint security systems and technology. It is an essential resource for all security and biometrics professionals, researchers, practitioners, developers, and systems administrators, and can serve as an easy-to-read reference for a graduate course on biometrics.Davide Maltoni is associate professor in the Department of Electronics, Informatics and Systems (DEIS) at the University of Bologna, where he also co-directs the Biometrics Systems Laboratory (BioLab).Dario Maio is full professor in the University of Bologna's DEIS and a co-director of the BioLab. He holds two patents on fingerprint liveness detection.Anil K. Jain is university-distinguished professor in the Department of Computer Science and Engineering at Michigan State University. He is a fellow of the IEEE, ACM and IAPR and holds six patents on algorithms for fingerprint recognition.Salil Prabhakar is the Chief Scientist of DigitalPersona Inc., a leading provider of fingerprint identity solutions for consumers, enterprises, and custom application developers.Key Topics\* Fingerprint individuality\* Fingerprint sensing \* Biometric fusion\* Synthetic fingerprint generation \* Minutiae detection\* Fingerprint system security \* Performance evaluation\* Feature extraction, matching, and indexing.

Condición: New. This comprehensive handbook provides in-depth coverage of the most recent advances and practices in fingerprint recognition. Readers will find authoritative coverage of all the major concepts, topics, and security methods associated with the subject. Num Pages: 510 pages, 34 black & white tables, biography. BIC Classification: UML; UYQ; UYQP; UYT. Category: (G) General (US: Trade). Dimension: 235 x 191 x 26. Weight in Grams: 957. . 2014. 2nd ed. 2009. Paperback. . . . .

Condición: New. 3rd ed. 2022 edition NO-PA16APR2015-KAP.

Condición: New.

Condición: New. This comprehensive handbook provides in-depth coverage of the most recent advances and practices in fingerprint recognition. Readers will find authoritative coverage of all the major concepts, topics, and security methods associated with the subject. Num Pages: 510 pages, 34 black & white tables, biography. BIC Classification: UML; UYQ; UYQP; UYT. Category: (G) General (US: Trade). Dimension: 235 x 191 x 26. Weight in Grams: 957. . 2014. 2nd ed. 2009. Paperback. . . . . Books ship from the US and Ireland.

Buch. Condición: Neu. Neuware -With their distinctiveness and stability over time, fingerprints continue to be the most widely used anatomical characteristic in systems that automatically recognize a person's identity.This fully updated third edition provides in-depth coverage of the state-of-the-art in fingerprint recognition readers, feature extraction, and matching algorithms and applications. Deep learning (resurgence beginning around 2012) has been a game changer for artificial intelligence and, in particular, computer vision and biometrics. Performance improvements (both recognition accuracy and speed) for most biometric modalities can be attributed to the use of deep neural networks along with availability of large training sets and powerful hardware. Fingerprint recognition has also been approached by deep learning, resulting in effective and efficient methods for automated recognition and for learning robust fixed-length representations. However, the tiny ridge details in fingerprints known as minutiae are still competitive with the powerful representations learned by huge neural networks trained on big data.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 548 pp. Englisch.

Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - With their distinctiveness and stability over time, fingerprints continue to be the most widely used anatomical characteristic in systems that automatically recognize a person's identity.This fully updated third edition provides in-depth coverage of the state-of-the-art in fingerprint recognition readers, feature extraction, and matching algorithms and applications. Deep learning (resurgence beginning around 2012) has been a game changer for artificial intelligence and, in particular, computer visionand biometrics. Performance improvements (both recognition accuracy and speed) for most biometric modalities can be attributed to the use of deep neural networks along with availability of large training sets and powerful hardware. Fingerprint recognition has also been approached by deep learning, resulting in effective and efficient methods for automated recognition and for learning robust fixed-length representations. However, the tiny ridge details in fingerprints known as minutiae are still competitive with the powerful representations learned by huge neural networks trained on big data.Features & Benefits:Reflects the progress made in automated techniques for fingerprint recognition over the past five decadesReviews the evolution of sensing technology: from bulky optical devices to in-display readers in smartphonesDedicates an entire new chapter to latent fingerprint recognition, which is nowadays feasible in 'lights-out' modeIntroduces classical and learning-based techniques for local orientation extraction, enhancement, and minutiae detectionProvides an updated review of presentation-attack-detection techniques and their performance evaluationDiscusses the evolution of minutiae matching from rich local descriptors to Minutiae Cylinder Code Presents the development of feature-based matching: from FingerCode to handcrafted textural features to deep featuresReviews fingerprint synthesis, including recent Generative Adversarial NetworksThe revised edition of this must-read reference, written by leading international researchers, covers all critical aspects of fingerprint security system design and technology. It is an essential resource for all security and biometrics professionals, researchers, practitioners, developers, and systems administrators, and can serve as an easy-to-read reference for an undergraduate or graduate course on biometrics. Davide Maltoni is full professor in the Department of Computer Science (DISI) at the University of Bologna, where he also co-directs the Biometrics Systems Laboratory (BioLab). Dario Maio is full professor in the DISI and a co-director of the BioLab. Anil K. Jain is university distinguished professor in the Department of Computer Science and Engineering at Michigan State University. Jianjiang Feng is associate professor in the Department of Automation at Tsinghua University.

Paperback. Condición: new. Paperback. A major new professional reference work on fingerprint security systems and technology from leading international researchers in the field. Handbook provides authoritative and comprehensive coverage of all major topics, concepts, and methods for fingerprint security systems. This unique reference work is an absolutely essential resource for all biometric security professionals, researchers, and systems administrators. This comprehensive handbook provides in-depth coverage of the most recent advances and practices in fingerprint recognition. Readers will find authoritative coverage of all the major concepts, topics, and security methods associated with the subject. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -With their distinctiveness and stability over time, fingerprints continue to be the most widely used anatomical characteristic in systems that automatically recognize a person's identity.This fully updated third edition provides in-depth coverage of the state-of-the-art in fingerprint recognition readers, feature extraction, and matching algorithms and applications. Deep learning (resurgence beginning around 2012) has been a game changer for artificial intelligence and, in particular, computer visionand biometrics. Performance improvements (both recognition accuracy and speed) for most biometric modalities can be attributed to the use of deep neural networks along with availability of large training sets and powerful hardware. Fingerprint recognition has also been approached by deep learning, resulting in effective and efficient methods for automated recognition and for learning robust fixed-length representations. However, the tiny ridge details in fingerprints known as minutiae are still competitive with the powerful representations learned by huge neural networks trained on big data.Features & Benefits:Reflects the progress made in automated techniques for fingerprint recognition over the past five decadesReviews the evolution of sensing technology: from bulky optical devices to in-display readers in smartphonesDedicates an entire new chapter to latent fingerprint recognition, which is nowadays feasible in 'lights-out' modeIntroduces classical and learning-based techniques for local orientation extraction, enhancement, and minutiae detectionProvides an updated review of presentation-attack-detection techniques and their performance evaluationDiscusses the evolution of minutiae matching from rich local descriptors to Minutiae Cylinder Code Presents the development of feature-based matching: from FingerCode to handcrafted textural features to deep featuresReviews fingerprint synthesis, including recent Generative Adversarial NetworksThe revised edition of this must-read reference, written by leading international researchers, covers all critical aspects of fingerprint security system design and technology. It is an essential resource for all security and biometrics professionals, researchers, practitioners, developers, and systems administrators, and can serve as an easy-to-read reference for an undergraduate or graduate course on biometrics. Davide Maltoni is full professor in the Department of Computer Science (DISI) at the University of Bologna, where he also co-directs the Biometrics Systems Laboratory (BioLab). Dario Maio is full professor in the DISI and a co-director of the BioLab. Anil K. Jain is university distinguished professor in the Department of Computer Science and Engineering at Michigan State University. Jianjiang Feng is associate professor in the Department of Automation at Tsinghua University. 548 pp. Englisch.

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. With their distinctiveness and stability over time, fingerprints continue to be the most widely used anatomical characteristic in systems that automatically recognize a person s identity.This fully updated third edition provides in-depth coverage of .

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Written with the same formula that made the success of the first edition, the book includes the most recent state-of-the-art techniques in the fieldProvides as enhanced and updated chapters covering sensor technology, performance evaluation, stand.