2014, ISBN: 9783642428401

[ED: Softcover], [PU: Springer / Springer Berlin Heidelberg / Springer, Berlin], Cross disciplinary biometric systems help boost the performance of the conventional systems. Not only is t… More...

[ED: Softcover], [PU: Springer / Springer Berlin Heidelberg / Springer, Berlin], Cross disciplinary biometric systems help boost the performance of the conventional systems. Not only is the recognition accuracy significantly improved, but also the robustness of the systems is greatly enhanced in the challenging environments, such as varying illumination conditions. By leveraging the cross disciplinary technologies, face recognition systems, fingerprint recognition systems, iris recognition systems, as well as image search systems all benefit in terms of recognition performance. Take face recognition for an example, which is not only the most natural way human beings recognize the identity of each other, but also the least privacy-intrusive means because people show their face publicly every day. Face recognition systems display superb performance when they capitalize on the innovative ideas across color science, mathematics, and computer science (e.g., pattern recognition, machine learning, and image processing). The novel ideas lead to the development of new color models and effective color features in color science; innovative features from wavelets and statistics, and new kernel methods and novel kernel models in mathematics; new discriminant analysis frameworks, novel similarity measures, and new image analysis methods, such as fusing multiple image features from frequency domain, spatial domain, and color domain in computer science; as well as system design, new strategies for system integration, and different fusion strategies, such as the feature level fusion, decision level fusion, and new fusion strategies with novel similarity measures. 2012. 2014. xvi, 228 S. XVI, 228 p. 235 mm Versandfertig in 6-10 Tagen, DE, [SC: 0.00], Neuware, gewerbliches Angebot, Offene Rechnung (Vorkasse vorbehalten)<

2014, ISBN: 3642428401

[EAN: 9783642428401], Neubuch, [PU: Springer Berlin Heidelberg Mai 2014], IRISRECOGNITION; BIOMETRICSYSTEMS; FACERECOGNITION; FINGERPRINTRECOGNITION; INTELLIGENTSYSTEMS, This item is prin… More...

[EAN: 9783642428401], Neubuch, [PU: Springer Berlin Heidelberg Mai 2014], IRISRECOGNITION; BIOMETRICSYSTEMS; FACERECOGNITION; FINGERPRINTRECOGNITION; INTELLIGENTSYSTEMS, This item is printed on demand - it takes 3-4 days longer - Neuware -Cross disciplinary biometric systems help boost the performance of the conventional systems. Not only is the recognition accuracy significantly improved, but also the robustness of the systems is greatly enhanced in the challenging environments, such as varying illumination conditions. By leveraging the cross disciplinary technologies, face recognition systems, fingerprint recognition systems, iris recognition systems, as well as image search systems all benefit in terms of recognition performance. Take face recognition for an example, which is not only the most natural way human beings recognize the identity of each other, but also the least privacy-intrusive means because people show their face publicly every day. Face recognition systems display superb performance when they capitalize on the innovative ideas across color science, mathematics, and computer science (e.g., pattern recognition, machine learning, and image processing). The novel ideas lead to the development of new color models and effective color features in color science; innovative features from wavelets and statistics, and new kernel methods and novel kernel models in mathematics; new discriminant analysis frameworks, novel similarity measures, and new image analysis methods, such as fusing multiple image features from frequency domain, spatial domain, and color domain in computer science; as well as system design, new strategies for system integration, and different fusion strategies, such as the feature level fusion, decision level fusion, and new fusion strategies with novel similarity measures. 244 pp. Englisch, Books<

2014, ISBN: 3642428401

[EAN: 9783642428401], Neubuch, [SC: 0.0], [PU: Springer Berlin Heidelberg], IRISRECOGNITION; BIOMETRICSYSTEMS; FACERECOGNITION; FINGERPRINTRECOGNITION; INTELLIGENTSYSTEMS, Druck auf Anfra… More...

[EAN: 9783642428401], Neubuch, [SC: 0.0], [PU: Springer Berlin Heidelberg], IRISRECOGNITION; BIOMETRICSYSTEMS; FACERECOGNITION; FINGERPRINTRECOGNITION; INTELLIGENTSYSTEMS, Druck auf Anfrage Neuware - Printed after ordering - Cross disciplinary biometric systems help boost the performance of the conventional systems. Not only is the recognition accuracy significantly improved, but also the robustness of the systems is greatly enhanced in the challenging environments, such as varying illumination conditions. By leveraging the cross disciplinary technologies, face recognition systems, fingerprint recognition systems, iris recognition systems, as well as image search systems all benefit in terms of recognition performance. Take face recognition for an example, which is not only the most natural way human beings recognize the identity of each other, but also the least privacy-intrusive means because people show their face publicly every day. Face recognition systems display superb performance when they capitalize on the innovative ideas across color science, mathematics, and computer science (e.g., pattern recognition, machine learning, and image processing). The novel ideas lead to the development of new color models and effective color features in color science; innovative features from wavelets and statistics, and new kernel methods and novel kernel models in mathematics; new discriminant analysis frameworks, novel similarity measures, and new image analysis methods, such as fusing multiple image features from frequency domain, spatial domain, and color domain in computer science; as well as system design, new strategies for system integration, and different fusion strategies, such as the feature level fusion, decision level fusion, and new fusion strategies with novel similarity measures., Books<

2014, ISBN: 3642428401

[EAN: 9783642428401], Neubuch, [SC: 0.0], [PU: Springer Berlin Heidelberg], BIOMETRICSYSTEMS; FACERECOGNITION; FINGERPRINTRECOGNITION; INTELLIGENTSYSTEMS; IRISRECOGNITION, Druck auf Anfra… More...

[EAN: 9783642428401], Neubuch, [SC: 0.0], [PU: Springer Berlin Heidelberg], BIOMETRICSYSTEMS; FACERECOGNITION; FINGERPRINTRECOGNITION; INTELLIGENTSYSTEMS; IRISRECOGNITION, Druck auf Anfrage Neuware - Cross disciplinary biometric systems help boost the performance of the conventional systems. Not only is the recognition accuracy significantly improved, but also the robustness of the systems is greatly enhanced in the challenging environments, such as varying illumination conditions. By leveraging the cross disciplinary technologies, face recognition systems, fingerprint recognition systems, iris recognition systems, as well as image search systems all benefit in terms of recognition performance. Take face recognition for an example, which is not only the most natural way human beings recognize the identity of each other, but also the least privacy-intrusive means because people show their face publicly every day. Face recognition systems display superb performance when they capitalize on the innovative ideas across color science, mathematics, and computer science (e.g., pattern recognition, machine learning, and image processing). The novel ideas lead to the development of new color models and effective color features in color science; innovative features from wavelets and statistics, and new kernel methods and novel kernel models in mathematics; new discriminant analysis frameworks, novel similarity measures, and new image analysis methods, such as fusing multiple image features from frequency domain, spatial domain, and color domain in computer science; as well as system design, new strategies for system integration, and different fusion strategies, such as the feature level fusion, decision level fusion, and new fusion strategies with novel similarity measures. 244 pp. Englisch, Books<

ISBN: 9783642428401

Cross disciplinary biometric systems help boost the performance of the conventional systems. Not only is the recognition accuracy significantly improved, but also the robustness of the sy… More...

Cross disciplinary biometric systems help boost the performance of the conventional systems. Not only is the recognition accuracy significantly improved, but also the robustness of the systems is greatly enhanced in the challenging environments, such as varying illumination conditions. By leveraging the cross disciplinary technologies, face recognition systems, fingerprint recognition systems, iris recognition systems, as well as image search systems all benefit in terms of recognition performance. Take face recognition for an example, which is not only the most natural way human beings recognize the identity of each other, but also the least privacy-intrusive means because people show their face publicly every day. Face recognition systems display superb performance when they capitalize on the innovative ideas across color science, mathematics, and computer science (e.g., pattern recognition, machine learning, and image processing). The novel ideas lead to the development of new color models and effective color features in color science; innovative features from wavelets and statistics, and new kernel methods and novel kernel models in mathematics; new discriminant analysis frameworks, novel similarity measures, and new image analysis methods, such as fusing multiple image features from frequency domain, spatial domain, and color domain in computer science; as well as system design, new strategies for system integration, and different fusion strategies, such as the feature level fusion, decision level fusion, and new fusion strategies with novel similarity measures. Books > Computers > Artificial Intelligence List_Books, [PU: Springer, Berlin/Heidelberg/New York, NY]<