Adaptive Biometric Systems : Recent Advances and Challenges / edited by Ajita Rattani, Fabio Roli, Eric Granger.
Material type: TextLanguage: İngilizce Series: Advances in Computer Vision and Pattern RecognitionPublisher: Cham : Springer International Publishing : Imprint: Springer, 2015Description: 1 online resourceContent type:- text
- computer
- online resource
- 9783319248653
- QH323.5
Item type | Current library | Home library | Collection | Call number | Status | Notes | Date due | Barcode | |
---|---|---|---|---|---|---|---|---|---|
E-Book | Merkez Kütüphane | Merkez Kütüphane | E-Kitap Koleksiyonu | QH323.5EBK (Browse shelf(Opens below)) | Geçerli değil-e-Kitap / Not applicable-e-Book | BİL | EBK00018 |
This timely and interdisciplinary volume presents a detailed overview of the latest advances and challenges remaining in the field of adaptive biometric systems. A broad range of techniques are provided from an international selection of pre-eminent authorities, collected together under a unified taxonomy and designed to be applicable to any pattern recognition system. Topics and features: Presents a thorough introduction to the concept of adaptive biometric systems, detailing their taxonomy, levels of adaptation, and open issues and challenges Reviews systems for adaptive face recognition that perform self-updating of facial models using operational (unlabeled) data Describes a novel semi-supervised training strategy known as fusion-based co-training Examines the characterization and recognition of human gestures in videos Discusses a selection of learning techniques that can be applied to build an adaptive biometric system Investigates procedures for handling temporal variance in facial biometrics due to aging Proposes a score-level fusion scheme for an adaptive multimodal biometric system This comprehensive text/reference will be of great interest to researchers and practitioners engaged in systems science, information security or biometrics. Postgraduate and final-year undergraduate students of computer engineering will also appreciate the coverage of intelligent and adaptive schemes for cutting-edge pattern recognition and signal processing in changing environments.
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