Biometric Systems
Because of the accelerating progress in biometrics research and the latest nation-state threats to security, this book's publication is not only timely but also much needed. This volume contains seventeen peer-reviewed chapters reporting the state of the art in biometrics research: security iss...
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Format: | Electronic Book Chapter |
Language: | English |
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Basel, Switzerland
MDPI - Multidisciplinary Digital Publishing Institute
2021
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Online Access: | DOAB: download the publication DOAB: description of the publication |
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020 | |a 9783036511283 | ||
020 | |a 9783036511290 | ||
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042 | |a dc | ||
072 | 7 | |a TB |2 bicssc | |
100 | 1 | |a Nanni, Loris |4 edt | |
700 | 1 | |a Berlin Brahnam, Sheryl |4 edt | |
700 | 1 | |a Nanni, Loris |4 oth | |
700 | 1 | |a Berlin Brahnam, Sheryl |4 oth | |
245 | 1 | 0 | |a Biometric Systems |
260 | |a Basel, Switzerland |b MDPI - Multidisciplinary Digital Publishing Institute |c 2021 | ||
300 | |a 1 electronic resource (352 p.) | ||
336 | |a text |b txt |2 rdacontent | ||
337 | |a computer |b c |2 rdamedia | ||
338 | |a online resource |b cr |2 rdacarrier | ||
506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
520 | |a Because of the accelerating progress in biometrics research and the latest nation-state threats to security, this book's publication is not only timely but also much needed. This volume contains seventeen peer-reviewed chapters reporting the state of the art in biometrics research: security issues, signature verification, fingerprint identification, wrist vascular biometrics, ear detection, face detection and identification (including a new survey of face recognition), person re-identification, electrocardiogram (ECT) recognition, and several multi-modal systems. This book will be a valuable resource for graduate students, engineers, and researchers interested in understanding and investigating this important field of study. | ||
540 | |a Creative Commons |f https://creativecommons.org/licenses/by/4.0/ |2 cc |4 https://creativecommons.org/licenses/by/4.0/ | ||
546 | |a English | ||
650 | 7 | |a Technology: general issues |2 bicssc | |
653 | |a online signature verification | ||
653 | |a shape contexts | ||
653 | |a function features | ||
653 | |a SC-DTW | ||
653 | |a symbolic representation | ||
653 | |a two-stage method | ||
653 | |a finger features | ||
653 | |a multimodal recognition | ||
653 | |a local coding | ||
653 | |a Gabor filter | ||
653 | |a LGS | ||
653 | |a human identification | ||
653 | |a biomarker | ||
653 | |a ECG | ||
653 | |a machine learning | ||
653 | |a Physionet | ||
653 | |a Lviv Biometric Dataset | ||
653 | |a biometry | ||
653 | |a identification | ||
653 | |a bloodstream | ||
653 | |a image recognition | ||
653 | |a multi-biometrics | ||
653 | |a bit planes | ||
653 | |a block | ||
653 | |a mutual information | ||
653 | |a cross-device | ||
653 | |a dorsal hand vein recognition | ||
653 | |a person re-identification | ||
653 | |a superpixel | ||
653 | |a temporally aligned pooling | ||
653 | |a walking cycle | ||
653 | |a automatic recognition | ||
653 | |a face | ||
653 | |a voice | ||
653 | |a body motion | ||
653 | |a autism spectrum disorder (ASD) | ||
653 | |a assessment | ||
653 | |a intervention | ||
653 | |a curve similarity | ||
653 | |a curve similarity model | ||
653 | |a curve similarity transformation | ||
653 | |a similarity distance | ||
653 | |a segmentation matching | ||
653 | |a evolutionary computation | ||
653 | |a finger vein recognition | ||
653 | |a hand vein recognition | ||
653 | |a contactless acquisition device | ||
653 | |a public vascular pattern dataset | ||
653 | |a biometric recognition performance evaluation | ||
653 | |a face verification | ||
653 | |a optical correlation | ||
653 | |a Hausdorff distance | ||
653 | |a image classification | ||
653 | |a face detection | ||
653 | |a depth map ensemble | ||
653 | |a filtering | ||
653 | |a geometric deep learning | ||
653 | |a ear detection | ||
653 | |a structured prediction | ||
653 | |a semantic segmentation | ||
653 | |a rotation equivariance | ||
653 | |a Gaussian mixture model | ||
653 | |a superpixels | ||
653 | |a face recognition systems | ||
653 | |a person identification | ||
653 | |a biometric systems | ||
653 | |a survey | ||
653 | |a automatic signature verification | ||
653 | |a touch-screen sensor | ||
653 | |a data quality | ||
653 | |a enrollment phase | ||
653 | |a performance assessment | ||
653 | |a augmented signature | ||
653 | |a security enhancement | ||
653 | |a mobile conditions | ||
653 | |a biometric recognition | ||
653 | |a visible light iris images | ||
653 | |a image quality assessment | ||
653 | |a image covariates | ||
653 | |a quality filtering | ||
653 | |a vascular biometric recognition | ||
653 | |a wrist vein recognition | ||
653 | |a contactless dataset | ||
653 | |a pattern recognition | ||
653 | |a infrared camera | ||
653 | |a non-contact devices | ||
653 | |a Scale-Invariant Feature Transform (SIFT®) | ||
653 | |a Speeded Up Robust Features (SURF®) | ||
653 | |a Oriented FAST and Rotated BRIEF (ORB) | ||
653 | |a fingerprint | ||
653 | |a presentation attack detection | ||
653 | |a deep learning | ||
856 | 4 | 0 | |a www.oapen.org |u https://mdpi.com/books/pdfview/book/4163 |7 0 |z DOAB: download the publication |
856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/76714 |7 0 |z DOAB: description of the publication |