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Biometric identification. --- Biometric person authentication --- Biometrics (Identification) --- Anthropometry --- Identification
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Biometric identification.. --- Biometric person authentication --- Biometrics (Identification) --- Anthropometry --- Identification
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Biometric identification. --- Optical pattern recognition. --- Optical data processing --- Pattern perception --- Perceptrons --- Visual discrimination --- Biometric person authentication --- Biometrics (Identification) --- Anthropometry --- Identification
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Biometric identification. --- Identification --- Pattern recognition systems. --- Computer networks --- Pattern classification systems --- Pattern recognition computers --- Pattern perception --- Computer vision --- Forensic identification --- Biometric person authentication --- Biometrics (Identification) --- Anthropometry --- Automation. --- Access control. --- Data sovereignty
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Biometric identification --- Digital forensic science. --- Technological innovations. --- Computer and network forensics --- Computer forensics --- Digital forensics --- Network forensics --- Electronic evidence --- Forensic sciences --- Digital preservation --- Biometric person authentication --- Biometrics (Identification) --- Anthropometry --- Identification
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This book highlights recent advances in smart cities technologies, with a focus on new technologies such as biometrics, blockchains, data encryption, data mining, machine learning, deep learning, cloud security, and mobile security. During the past five years, digital cities have been emerging as a technology reality that will come to dominate the usual life of people, in either developed or developing countries. Particularly, with big data issues from smart cities, privacy and security have been a widely concerned matter due to its relevance and sensitivity extensively present in cybersecurity, healthcare, medical service, e-commercial, e-governance, mobile banking, e-finance, digital twins, and so on. These new topics rises up with the era of smart cities and mostly associate with public sectors, which are vital to the modern life of people. This volume summarizes the recent advances in addressing the challenges on big data privacy and security in smart cities and points out the future research direction around this new challenging topic.
Cities and towns. --- Big data. --- Smart cities. --- Cities and towns --- Data sets, Large --- Large data sets --- Data sets --- Global cities --- Municipalities --- Towns --- Urban areas --- Urban systems --- Human settlements --- Sociology, Urban --- Data protection --- Cooperating objects (Computer systems). --- Machine learning. --- Biometric identification. --- Big Data. --- Privacy. --- Cyber-Physical Systems. --- Machine Learning. --- Biometrics. --- Law and legislation. --- Biometric person authentication --- Biometrics (Identification) --- Anthropometry --- Identification --- Learning, Machine --- Artificial intelligence --- Machine theory --- Habeas data --- Privacy, Right of
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This book explores intrinsic and human body part biometrics and biometrics of human physiological activities, invisible to the naked eye. This includes, for instance, brain structures, skeleton morphology, heart activity, etc. These human body parts can only be visualized using specific imaging techniques or sensors, commonly employed in the biomedical engineering field. As such, the book connects two fields, namely biometric security and biomedical engineering. The book is suitable for advanced graduate and postgraduate students, engineers and researchers, especially in Signal and Image Processing, Biometrics, and Biomedical Engineering.
Biometric identification. --- Biometric person authentication --- Biometrics (Identification) --- Anthropometry --- Identification --- Biomedical engineering. --- Clinical engineering --- Medical engineering --- Bioengineering --- Biophysics --- Engineering --- Medicine --- Signal processing. --- Image processing. --- Speech processing systems. --- Biometrics (Biology). --- Pattern recognition. --- Signal, Image and Speech Processing. --- Biometrics. --- Biomedical Engineering and Bioengineering. --- Pattern Recognition. --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- Biological statistics --- Biology --- Biometrics (Biology) --- Biostatistics --- Biomathematics --- Statistics --- Computational linguistics --- Electronic systems --- Information theory --- Modulation theory --- Oral communication --- Speech --- Telecommunication --- Singing voice synthesizers --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing --- Processing, Signal --- Information measurement --- Signal theory (Telecommunication) --- Statistical methods
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This book emphasizes recent advances in the creation of biometric identification systems for various applications in the field of human activity. The book displays the problems that arise in modern systems of biometric identification, as well as the level of development and prospects for the introduction of biometric technologies. The authors classify biometric technologies into two groups, distinguished according to the type of biometric characteristics used. The first group uses static biometric parameters: fingerprints, hand geometry, retina pattern, vein pattern on the finger, etc. The second group uses dynamic parameters for identification: the dynamics of the reproduction of a signature or a handwritten keyword, voice, gait, dynamics of work on the keyboard, etc. The directions of building information systems that use automatic personality identification based on the analysis of unique biometric characteristics of a person are discussed. The book is intended for professionals working and conducting research in the field of intelligent information processing, information security, and robotics and in the field of real-time identification systems. The book contains examples and problems/solutions throughout. Presents recent advances in the creation of biometric identification systems for various applications; Classifies biometrics into two groups - static and dynamic - and discusses developing for each; Relevant for students, researchers, and professionals in intelligent information processing, security, and robotics.
Signal processing. --- Image processing. --- Speech processing systems. --- Biometrics (Biology). --- System safety. --- Signal, Image and Speech Processing. --- Biometrics. --- Security Science and Technology. --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing --- Processing, Signal --- Information measurement --- Signal theory (Telecommunication) --- Safety, System --- Safety of systems --- Systems safety --- Accidents --- Industrial safety --- Systems engineering --- Biological statistics --- Biology --- Biometrics (Biology) --- Biostatistics --- Biomathematics --- Statistics --- Computational linguistics --- Electronic systems --- Information theory --- Modulation theory --- Oral communication --- Speech --- Telecommunication --- Singing voice synthesizers --- Prevention --- Statistical methods --- Biometric identification. --- Biometry. --- Data mining. --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Biometric person authentication --- Biometrics (Identification) --- Anthropometry --- Identification
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This timely text/reference presents a broad overview of advanced deep learning architectures for learning effective feature representation for perceptual and biometrics-related tasks. The text offers a showcase of cutting-edge research on the use of convolutional neural networks (CNN) in face, iris, fingerprint, and vascular biometric systems, in addition to surveillance systems that use soft biometrics. Issues of biometrics security are also examined. Topics and features: Addresses the application of deep learning to enhance the performance of biometrics identification across a wide range of different biometrics modalities Revisits deep learning for face biometrics, offering insights from neuroimaging, and provides comparison with popular CNN-based architectures for face recognition Examines deep learning for state-of-the-art latent fingerprint and finger-vein recognition, as well as iris recognition Discusses deep learning for soft biometrics, including approaches for gesture-based identification, gender classification, and tattoo recognition Investigates deep learning for biometrics security, covering biometrics template protection methods, and liveness detection to protect against fake biometrics samples Presents contributions from a global selection of pre-eminent experts in the field representing academia, industry and government laboratories Providing both an accessible introduction to the practical applications of deep learning in biometrics, and a comprehensive coverage of the entire spectrum of biometric modalities, this authoritative volume will be of great interest to all researchers, practitioners and students involved in related areas of computer vision, pattern recognition and machine learning. Dr. Bir Bhanu is Bourns Presidential Chair, Distinguished Professor of Electrical and Computer Engineering and the Director of the Center for Research in Intelligent Systems at the University of California at Riverside, USA. Some of his other Springer publications include the titles Video Bioinformatics, Distributed Video Sensor Networks, and Human Recognition at a Distance in Video. Dr. Ajay Kumar is an Associate Professor in the Department of Computing at the Hong Kong Polytechnic University.
Biometric identification. --- Machine learning. --- Learning, Machine --- Biometric person authentication --- Biometrics (Identification) --- Computer science. --- Artificial intelligence. --- Biometrics (Biology). --- Computer science --- Computer mathematics. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Biometrics. --- Mathematical Applications in Computer Science. --- Signal, Image and Speech Processing. --- Mathematics. --- Artificial intelligence --- Machine theory --- Anthropometry --- Identification --- Artificial Intelligence. --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Computer science—Mathematics. --- Signal processing. --- Image processing. --- Speech processing systems. --- Computational linguistics --- Electronic systems --- Information theory --- Modulation theory --- Oral communication --- Speech --- Telecommunication --- Singing voice synthesizers --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing --- Processing, Signal --- Information measurement --- Signal theory (Telecommunication) --- Computer mathematics --- Mathematics --- Biological statistics --- Biology --- Biometrics (Biology) --- Biostatistics --- Biomathematics --- Statistics --- Statistical methods
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The book provides insights into the Second International Conference on Computer Vision & Image Processing (CVIP-2017) organized by Department of Computer Science and Engineering of Indian Institute of Technology Roorkee. The book presents technological progress and research outcomes in the area of image processing and computer vision. The topics covered in this book are image/video processing and analysis; image/video formation and display; image/video filtering, restoration, enhancement and super-resolution; image/video coding and transmission; image/video storage, retrieval and authentication; image/video quality; transform-based and multi-resolution image/video analysis; biological and perceptual models for image/video processing; machine learning in image/video analysis; probability and uncertainty handling for image/video processing; motion and tracking; segmentation and recognition; shape, structure and stereo.
Computer vision --- Engineering. --- Image processing. --- Biometrics (Biology). --- Signal, Image and Speech Processing. --- Image Processing and Computer Vision. --- Biometrics. --- Biological statistics --- Biology --- Biometrics (Biology) --- Biostatistics --- Biomathematics --- Statistics --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing --- Construction --- Industrial arts --- Technology --- Statistical methods --- Computer vision. --- Machine vision --- Vision, Computer --- Artificial intelligence --- Image processing --- Pattern recognition systems --- Signal processing. --- Speech processing systems. --- Optical data processing. --- Optical computing --- Visual data processing --- Bionics --- Electronic data processing --- Integrated optics --- Photonics --- Computers --- Computational linguistics --- Electronic systems --- Information theory --- Modulation theory --- Oral communication --- Speech --- Telecommunication --- Singing voice synthesizers --- Processing, Signal --- Information measurement --- Signal theory (Telecommunication) --- Optical equipment --- Biometric identification. --- Signal, Speech and Image Processing . --- Computer Vision. --- Biometric person authentication --- Biometrics (Identification) --- Anthropometry --- Identification
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