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Reliable Face Recognition Methods

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Reliable Face Recognition Methods
Lowest price (incl. delivery)
14 324,00 JPY
Typical price1 124,44 PLN
Lowest (90 days)89,99 PLN
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Last updatedil y a 1 semaine
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2026-08-08 2026-08-15
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Mis à jour lePrix
2026-08-0889,99
2026-08-1589,99
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SP SpringerNatureLink Shop INT 14 299,00 JPY 25,00 JPY 14 324,00 JPY Disponible il y a 5 jours View offer
SP Springer Nature Author 14 299,00 JPY 19,00 JPY 14 318,00 JPY Disponible il y a 1 semaine View offer
SP SpringerNatureLink Shop INT 99,99 USD free 99,99 USD Disponible il y a 5 jours View offer
SP SpringerNatureLink Shop INT 109,99 USD 29,00 USD 138,99 USD Disponible il y a 5 jours View offer
SP SpringerNatureLink Shop INT 109,99 USD 25,00 USD 134,99 USD Disponible il y a 5 jours View offer
SP SpringerNatureLink Shop INT 109,99 USD 19,00 USD 128,99 USD Disponible il y a 5 jours View offer
SP SpringerNatureLink Shop INT 118,00 EUR 19,00 EUR 137,00 EUR Disponible il y a 5 jours View offer

Les prix et la disponibilité peuvent changer. Dernière mise à jour: 08.08.2026 23:23.

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One of the challenges for computational intelligence and biometrics is to understand how people process and recognize faces and to develop automated and reliable face recognition systems. Biometrics has become the major component in the complex decision making process associated with security applications. The many challenges addressed for face detection and authentication include cluttered environments, occlusion and disguise, temporal changes, robust training and open set testing. Reliable Face Recognition Methods seeks to comprehensively address the face recognition problem while gaining new insights from complementary fields of endeavor such as neurosciences, statistics, signal and image processing, computer vision, machine learning and data mining. This book examines the evolution of research surrounding the field to date, explores new directions, and offers specific guidance on the most promising venues for future research and development. Endorsements by: Ruud Bolle (IBM), John Daugman (Cambridge University, UK), David Zhang (Hong Kong Polytechnic University, China), Stan Li (Chinese Academy of Sciences, China), Tom Huang (University of Illinois, USA).

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