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sarangi partha pratim (curatore); panda madhumita (curatore); mishra subhashree (curatore); mishra bhabani shankar prasad (curatore); majhi banshidhar (curatore) - machine learning for biometrics

Machine Learning for Biometrics Concepts, Algorithms and Applications

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Lingua: Inglese
Pubblicazione: 01/2022

Note Editore

Machine Learning for Biometrics: Concepts, Algorithms and Applications highlights the fundamental concepts of machine learning, processing and analyzing data from biometrics and provides a review of intelligent and cognitive learning tools which can be adopted in this direction. Each chapter of the volume is supported by real-life case studies, illustrative examples and video demonstrations. The book elucidates various biometric concepts, algorithms and applications with machine intelligence solutions, providing guidance on best practices for new technologies such as e-health solutions, Data science, Cloud computing, and Internet of Things, etc.

In each section, different machine learning concepts and algorithms are used, such as different object detection techniques, image enhancement techniques, both global and local feature extraction techniques, and classifiers those are commonly used data science techniques. These biometrics techniques can be used as tools in Cloud computing, Mobile computing, IOT based applications, and e-health care systems for secure login, device access control, personal recognition and surveillance.

  • Covers different machine intelligence concepts, algorithms and applications in the field of cybersecurity, e-health monitoring, secure cloud computing and secure IOT based operations
  • Explores advanced approaches to improve recognition performance of biometric systems with the use of recent machine intelligence techniques
  • Introduces detection or segmentation techniques to detect biometric characteristics from the background in the input sample


1. Fundamentals of Biometrics and reviews of different biometrics and multimodal biometrics 2. Detection techniques of different biometric traits 3. Preprocessing using Machine learning approaches 4. Feature extraction and selection using Machine learning approaches 5. Recognition (Verification and Identification) techniques 6. Behavioral biometrics 7. Biometrics in Forensic Identification 8. Biometric cryptography (Bio-Cryptography) 9. Multimodal Biometrics 10. Security Applications


Dr. Partha Pratim Sarangi, is working as Professor in Computer Sc. & Engineering at Seemanta Engineering College, Jharpokharia, Odisha, INDIA. He has received his Ph.D. in Computer Science from KIIT University, Bhubaneswar, Odisha. His current research interests include Pattern Recognition, Soft computing, Biometrics, Computer Vision, and Data Science. He has already published about 22 research papers in refereed journals and conferences.
Ms. Madhumita Panda, is working as Assistant Professor in Master in Computer Applications at Seemanta Engineering College, Jharpokharia, Odisha. She has received his M.Tech in Computer Science from NIT Rourkela and continuing her Ph.D. from North Orissa University, Baripada, Odisha. Her current research interests include Pattern Recognition, Soft computing, Biometrics, Software Engineering. She has already published 2 book chapters and about 10 research papers in refereed journals and conferences.
Dr. Subhashree Mishra, is working as an Assistant Professor in School of Electronics Engineering at KIIT University, Bhubaneswar. She has completed her Master and PhD from KIIT University respectively. Her research interest includes Machine Learning, Communication Engineering, Image Processing and Soft Computing. She has published around 15 research articles and 4 Book chapters in referred journals and conferences. Currently she is guiding 2 PhD scholars.
Dr. Bhabani Shankar Prasad Mishra born in Talcher, Odisha, India in 1981. He received the B.Tech. in Computer Science and Engineering from Biju Pattanaik Technical University, Odisha in 2003, M.Tech. degree in Computer Science and Engineering from the KIIT University, in 2003, Ph.D. degree in Computer Science from F.M.University, Balasore,Odisha, India, in 2011 and Post Doc in 2013 from Soft Computing Laboratory, Yansei University, South Korea .

Currently he is working as an Associate Professor and Dean at School of Computer Engineering, KIIT University, Bhubaneswar, Odisha, India. His research interest includes Pattern Reorganization, Data Mining, Soft Computing, Big Data and Machine Learning. He has published more than 80 research articles in reputed Journal and Conferences, has edited more than five books of current importance. Under his guidance, 2 PhD scholars are already been awarded;

Dr. Mishra was the recipient of the Gold Medal and Silver Medal during his M.Tech for the best Post Graduate in the University. He is the member of different technical bodies ISTE, CSI and IET.
Prof. Banshidhar Majhi has three years of industry experience and more than 28 years of teaching and research experience in the field of Computer Science and Engineering. He is associated with NIT Rourkela since 1991 and presently serving as the Director IIITDM since July 2017. He has served in various administrative positions as HOD, Dean (Academic), Chairman, Automation Cell. He has been serving as members of various accreditation committees like the NBA and NAAC.

He has guided 17 Ph.D. scholars and 8 MS (research) students in addition to more than 150 M. Tech. theses. He has 80 research publications in peer reviewed journals and more than 150 publications in conferences of repute. He is a Senior Member IEEE, Fellow IETE, Fellow IE (India), Life Member of Computer Society of India. For his outstanding contributions in Engineering and Technology, Govt. of Odisha has conferred on him "Samanta Chandra Sekhar award in 2016. Prof. Majhi puts his best effort whatever he does and believes in terminology "Efforts never Fail .

As the Director, Prof. Majhi's single point agenda is to make IIITDM as a centre of excellence in design centric engineering education and make it as a destination for quality students and faculty to achieve their potential.

Altre Informazioni



Condizione: Nuovo
Collana: Cognitive Data Science in Sustainable Computing
Dimensioni: 229 x 152 mm
Formato: Brossura
Pagine Arabe: 264

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