LEADER 05620nam 22007575 450 001 9910799228903321 005 20240326102932.0 010 $a9783031435676 010 $a3031435672 024 7 $a10.1007/978-3-031-43567-6 035 $a(MiAaPQ)EBC31051230 035 $a(Au-PeEL)EBL31051230 035 $a(DE-He213)978-3-031-43567-6 035 $a(CKB)29510094900041 035 $a(OCoLC)1416747572 035 $a(EXLCZ)9929510094900041 100 $a20231229d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aHandbook of Face Recognition /$fedited by Stan Z. Li, Anil K. Jain, Jiankang Deng 205 $a3rd ed. 2024. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2024. 215 $a1 online resource (473 pages) 311 08$aPrint version: Li, Stan Z. Handbook of Face Recognition Cham : Springer International Publishing AG,c2024 9783031435669 327 $aPart I: Introduction and Background -- 1. Overview on Face recognition -- 2. Historical Developments and Challenges -- 3. Applications -- Part II: Fundamentals of Deep Neural Networks -- 4. Overview on Deep Learning for FR -- 5. Deep Neural Network Architecture Design -- 6. Loss Function Design -- 7. Auto-Encoders -- 8. Convolutional Neural Networks -- 9. Generative Adversarial Networks -- 10. Transfer Learning and Domain Adaptation -- 11. Deep Learning with Big/Small Data -- 12. Model Compression and Speedup -- 13. Programming Platforms for Deep Learning -- Part III: Face Recognition by Deep Neural Networks -- 14. Overview on Face Recognition Methods -- 15. Preprocessing Methods -- 16. Face Localization Detection -- 17. Face Localization Landmark -- 18. Visual Face Recognition -- 19. Multispectral Face Recognition -- 20. Fusion for Face Recognition. 330 $aThe history of computer-aided face recognition dates to the 1960s, yet the problem of automatic face recognition ? a task that humans perform routinely and effortlessly in our daily lives ? still poses great challenges, especially in unconstrained conditions. This highly anticipated new edition provides a comprehensive account of face recognition research and technology, spanning the full range of topics needed for designing operational recognition systems. After a thorough introduction, each subsequent chapter focuses on a specific topic, reviewing background information, up-to-date techniques, and recent results, as well as offering challenges and future directions. Topics and features: Fully updated, revised, and expanded, covering the entire spectrum of concepts, methods, and algorithms for automated detection and recognition systems Provides comprehensive coverage of face detection, alignment, feature extraction, and recognitiontechnologies, and issues in evaluation, systems, security, and applications Contains numerous step-by-step algorithms Describes a broad range of applications from person verification, surveillance, and security, to entertainment Presents contributions from an international selection of preeminent experts Integrates numerous supporting graphs, tables, charts, and performance data This practical and authoritative reference is an essential resource for researchers, professionals and students involved in image processing, computer vision, biometrics, security, Internet, mobile devices, human-computer interface, E-services, computer graphics and animation, and the computer game industry. Dr. Stan Z. Li is Chair Professor of Artificial Intelligence at Westlake University, Hangzhou, China. His Springer titles include Encyclopedia of Biometrics (with Dr. Jain) and Handbook of Remote Biometrics, among others. Dr. Anil K. Jain is a University Distinguished Professor in the Department of Computer Science and Engineering at Michigan State University, USA. His Springer titles include Introduction to Biometrics and Handbook of Fingerprint Recognition, among others. Jiankang Deng is a researcher and honorary lecturer at the Department of Computing, Imperial College London, UK. He is one of the main contributors to the widely used open-source platform Insight face. 606 $aBiometric identification 606 $aMachine learning 606 $aImage processing$xDigital techniques 606 $aComputer vision 606 $aData protection 606 $aPattern recognition systems 606 $aForensic sciences 606 $aBiometrics 606 $aMachine Learning 606 $aComputer Imaging, Vision, Pattern Recognition and Graphics 606 $aData and Information Security 606 $aAutomated Pattern Recognition 606 $aForensic Science 615 0$aBiometric identification. 615 0$aMachine learning. 615 0$aImage processing$xDigital techniques. 615 0$aComputer vision. 615 0$aData protection. 615 0$aPattern recognition systems. 615 0$aForensic sciences. 615 14$aBiometrics. 615 24$aMachine Learning. 615 24$aComputer Imaging, Vision, Pattern Recognition and Graphics. 615 24$aData and Information Security. 615 24$aAutomated Pattern Recognition. 615 24$aForensic Science. 676 $a006.42 700 $aLi$b Stan Z$028533 701 $aJain$b Anil K$08853 701 $aDeng$b Jiankang$01586129 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910799228903321 996 $aHandbook of Face Recognition$93872404 997 $aUNINA LEADER 02325nas 2200601- 450 001 9910141715503321 005 20241223110808.0 011 $a2197-4365 035 $a(OCoLC)889117161 035 $a(CKB)2560000000154816 035 $a(CONSER)--2014254728 035 $a(MiFhGG)02N8 035 $a(MiAaPQ)2034794 035 $a(DE-599)ZDB2785482-6 035 $a(EXLCZ)992560000000154816 100 $a20140825a20149999 --- a 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aBioresources and bioprocessing 210 1$aHeidelberg, Germany :$cSpringer-Verlag, GmbH,$d2014- 215 $a1 online resource 300 $aRefereed/Peer-reviewed 330 $aBioresources and Bioprocessing (BRBP) aims at providing an international academic platform for exchanging views on and promoting research to support bioresource development, processing and utilization in a sustainable manner. 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