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06583nam a22002417a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
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CUTN |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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20231130164108.0 |
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231130b |||||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9780367422448 |
| 041 ## - LANGUAGE CODE |
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| Language |
English |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Edition number |
23 |
| Classification number |
006.248 |
| Item number |
JAS |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Jaswal, Gaurav |
| 245 ## - TITLE STATEMENT |
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| Title |
AI and Deep Learning in Biometric Security : |
| Remainder of title |
Trends, Potential, and Challenges / |
| Statement of responsibility, etc |
Edited By Gaurav Jaswal, Vivek Kanhangad, & Raghavendra Ramachandra. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
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| Place of publication, distribution, etc |
Boca Raton : |
| Name of publisher, distributor, etc |
CRC Press, Taylor & Francis Group, |
| Date of publication, distribution, etc |
2021. |
| 300 ## - PHYSICAL DESCRIPTION |
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| Extent |
xiii, 364 pages : |
| Other physical details |
illustrations (black and white) ; |
| Dimensions |
25 cm. |
| 500 ## - GENERAL NOTE |
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| General note |
This book provides an in-depth overview of artificial intelligence and deep learning approaches with case studies to solve problems associated with biometric security such as authentication, indexing, template protection, spoofing attack detection, ROI detection, gender classification etc.<br/><br/>This text highlights a showcase of cutting-edge research on the use of convolution neural networks, autoencoders, recurrent convolutional neural networks in face, hand, iris, gait, fingerprint, vein, and medical biometric traits. It also provides a step-by-step guide to understanding deep learning concepts for biometrics authentication approaches and presents an analysis of biometric images under various environmental conditions.<br/><br/>This book is sure to catch the attention of scholars, researchers, practitioners, and technology aspirants who are willing to research in the field of AI and biometric security. |
| 505 ## - FORMATTED CONTENTS NOTE |
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| Contents |
TABLE OF CONTENTS |
| Title |
Chapter 1 Deep Learning-Based Hyperspectral Multimodal Biometric<br/><br/>Authentication System Using Palmprint and Dorsal Hand Vein<br/><br/>Shuping Zhao, Wei Nie, and Bob Zhang<br/><br/>Chapter 2 Cancelable Biometrics for Template Protection: Future<br/><br/>Directives with Deep Learning<br/><br/>Avantika Singh, Gaurav Jaswal, and Aditya Nigam<br/><br/>Chapter 3 On Training Generative Adversarial Network for Enhancement<br/><br/>of Latent Fingerprints<br/><br/>Indu Joshi, Adithya Anand, Sumantra Dutta Roy, and Prem Kumar Kalra<br/><br/>Chapter 4 DeepFake Face Video Detection Using Hybrid Deep Residual<br/><br/>Networks and LSTM Architecture<br/><br/>Semih Yavuzkilic, Zahid Akhtar, Abdulkadir Sengur, and Kamran Siddique<br/><br/>Chapter 5 Multi-spectral Short-Wave Infrared Sensors and Convolutional<br/><br/>Neural Networks for Biometric Presentation Attack Detection<br/><br/>Marta Gomez-Barrero, Ruben Tolosana, Jascha Kolberg, and Christoph Busch<br/><br/>Chapter 6 AI-Based Approach for Person Identification Using ECG<br/><br/>Biometric<br/><br/>Amit Kaul, A.S. Arora, and Sushil Chauhan<br/><br/>Chapter 7 Cancelable Biometric Systems from Research to Reality:<br/><br/>The Road Less Travelled<br/><br/>Harkeerat Kaur and Pritee Khanna<br/><br/> <br/><br/>Chapter 8 Gender Classification under Eyeglass Occluded Ocular Region:<br/><br/>An Extensive Study Using Multi-spectral Imaging<br/><br/>Narayan Vetrekar, Raghavendra Ramachandra, Kiran Raja, and R. S. Gad<br/><br/>Chapter 9 Investigation of the Fingernail Plate for Biometric<br/><br/>Authentication using Deep Neural Networks<br/><br/>Surabhi Hom Choudhury, Amioy Kumar, and Shahedul Haque Laskar<br/><br/>Chapter 10 Fraud Attack Detection in Remote Verification Systems for<br/><br/>Non-enrolled Users<br/><br/>Ignacio Viedma, Sebastian Gonzalez, Ricardo Navarro, and Juan Tapia<br/><br/>Chapter 11 Indexing on Biometric Databases<br/><br/>Geetika Arora, Jagdiah C. Joshi, Karunesh K. Gupta, and Kamlesh Tiwari<br/><br/>Chapter 12 Iris Segmentation in the Wild Using Encoder-Decoder-Based<br/><br/>Deep Learning Techniques<br/><br/>Shreshth Saini, Divij Gupta, Ranjeet Ranjan Jha, Gaurav Jaswal, and Aditya Nigam<br/><br/>Chapter 13 PPG-Based Biometric Recognition: Opportunities with<br/><br/>Machine and Deep Learning<br/><br/>Amit Kaul and Akhil Walia<br/><br/>Chapter 14 Current Trends of Machine Learning Techniques in Biometrics<br/><br/>and its Applications<br/><br/>B. S. Maaya and T. Asha |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc |
EDITORS Biography<br/>Dr. Gaurav Jaswal is currently working as Project Scientist, Electrical Engineering at National Agri-Food Biotechnology Institute Mohali. Prior to this, he was Research Associate, School of Computing and Electrical Engineering, Indian Institute of Technology Mandi, India. He received M.Tech and Ph.D degree in Electrical Engineering from National Institute of Technology Hamirpur in 2018. His research interests are in the areas of multimodal biometrics, biomedical signal processing and deep learning. He regularly reviews papers for various international journals including IEEE Transactions on Information Forensics and Security (TIFS), IEEE Transactions on Biometrics, Behavior, and Identity Science (T-BIOM), IET Biometrics. Dr. Vivek Kanhangad is currently working as Associate Professor, Department of Electrical Engineering, Indian Institute of Technology Indore since Feb, 2012. Prior to this, he was Visiting Assistant Professor, International Institute of Information Technology Bangalore (Jun 2010-Dec 2012). He received Ph.D. from the Hong Kong Polytechnic University in 2010. Prior to joining Hong Kong PolyU, he received M.Tech. degree in Electrical Engineering from Indian Institute of Technology Delhi, in 2006 and worked for Motorola India Electronics Ltd, Bangalore for a while. His research interests are in the overlapping areas of digital signal and image processing, pattern recognition with focus on biometrics and biomedical applications. He regularly reviews papers for various international journals including IEEE Transactions on Information Forensics and Security (TIFS), IEEE Transactions on Cybernetics, IEEE Transactions on Human-Machine Systems and Elsevier journals - Pattern Recognition and Pattern Recognition Letters. Dr. Raghavendra Ramachandra is currently working as a Professor in Department of Information Security and Communication Technology (IIK). He is member of Norwegian Biometrics Laboratory at NTNU Gjøvik. He received B.E (Electronics and Communication) from University of Mysore, India. M.Tech (Digital Electronics and Advance Communication Systems) from Visvesvaraya Technological University, India. Ph.D. (Computer Science with specialization of Pattern Recognition and Image Processing) from the University of Mysore, India and Telcom SudParis, France. His research interest includes Pattern Recognition, Image and video analytics, Biometrics, Human Behaviour Analysis, Video Surviellance, Health Biometrics, and Smartphone Authentication. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Artificial intelligence Biometric identification Identification biométrique Intelligence artificielle artificial intelligence |
| 690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN) |
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| Department Name |
COMPUTER SCIENCE |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Kanhangad, Vivek & Ramachandra, Raghavendra. |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
General Books |
