Deep Learning
- 1st Edition, Volume 48 - February 28, 2023
- Imprint: Academic Press
- Editors: Arni S.R. Srinivasa Rao, Venu Govindaraju, C.R. Rao
- Language: English
- Hardback ISBN:9 7 8 - 0 - 4 4 3 - 1 8 4 3 0 - 7
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 1 8 4 3 1 - 4
Deep Learning, Volume 48 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of timel… Read more
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Request a sales quoteDeep Learning, Volume 48 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of timely topics, including Generative Adversarial Networks for Biometric Synthesis, Data Science and Pattern Recognition, Facial Data Analysis, Deep Learning in Electronics, Pattern Recognition, Computer Vision and Image Processing, Mechanical Systems, Crop Technology and Weather, Manipulating Faces for Identity Theft via Morphing and Deepfake, Biomedical Engineering, and more.
- Provides the authority and expertise of leading contributors from an international board of authors
- Presents the latest release in the Handbook of Statistics series
- Includes the latest information on Deep Learning
Statisticians, mathematicians and students
- Cover image
- Title page
- Table of Contents
- Copyright
- Contributors
- Preface
- Section I: Foundations
- Chapter 1: Exact deep learning machines
- Abstract
- 1: Introduction
- 2: EDLM constructions
- 3: Conclusions
- References
- Chapter 2: Multiscale representation learning for biomedical analysis
- Abstract
- 1: Introduction
- 2: Representation learning: Background
- 3: Multiscale embedding motivation
- 4: Theoretical framework
- 5: Experiments, results, and discussion
- 6: Conclusion and future work
- References
- Chapter 3: Adversarial attacks and robust defenses in deep learning
- Abstract
- 1: Introduction
- 2: Adversarial attacks
- 3: On-manifold robustness
- 4: Knowledge distillation-based defenses
- 5: Defenses for object detector
- 6: Reverse engineering of deceptions via residual learning
- Acknowledgments
- References
- Section II: Advanced Methods
- Chapter 4: Deep metric learning for computer vision: A brief overview
- Abstract
- 1: Introduction
- 2: Background
- 3: Pair-based formulation
- 4: Proxy-based methods
- 5: Regularizations
- 6: Conclusion
- References
- Chapter 5: Source distribution weighted multisource domain adaptation without access to source data
- Abstract
- 1: Introduction
- 2: Related works
- 3: Problem setting
- 4: Practical motivation
- 5: Overall framework of DECISION (Ahmed et al., 2021)—A review
- 6: Theoretical insights
- 7: Source distribution dependent weights (DECISION-mlp)
- 8: Proof of Lemma 1
- 9: Experiments
- 10: Conclusions and future work
- References
- Section III: Transformative Applications
- Chapter 6: Deep learning methods for scientific and industrial research
- Abstract
- 1: Introduction
- 2: Data and methods
- 3: Applications of DL techniques for multi-disciplinary studies
- 4: Discussion and future prospects
- Acknowledgments
- References
- Chapter 7: On bias and fairness in deep learning-based facial analysis
- Abstract
- 1: Introduction
- 2: Tasks in facial analysis
- 3: Facial analysis databases for bias study
- 4: Evaluation metrics
- 5: Fairness estimation and analysis
- 6: Fair algorithms and bias mitigation
- 7: Meta-analysis of algorithms
- 8: Topography of commercial systems and patents
- 9: Open challenges
- 10: Discussion
- Acknowledgment
- References
- Chapter 8: Manipulating faces for identity theft via morphing and deepfake: Digital privacy
- Abstract
- 1: Introduction
- 2: Identity manipulation techniques
- 3: Identity manipulation datasets
- 4: Identity attack detection algorithms
- 5: Open challenges
- 6: Conclusion
- References
- Index
- Edition: 1
- Volume: 48
- Published: February 28, 2023
- No. of pages (Hardback): 270
- No. of pages (eBook): 270
- Imprint: Academic Press
- Language: English
- Hardback ISBN: 9780443184307
- eBook ISBN: 9780443184314
AS
Arni S.R. Srinivasa Rao
Arni S.R. Srinivasa Rao works in pure mathematics, applied mathematics, probability, and artificial intelligence and applications in medicine. He is a Professor at the Medical College of Georgia, Augusta University, U.S.A, and the Director of the Laboratory for Theory and Mathematical Modeling housed within the Division of Infectious Diseases, Medical College of Georgia, Augusta, U.S.A. Previously, Dr. Rao conducted research and/or taught at Mathematical Institute, University of Oxford (2003, 2005-07), Indian Statistical Institute (1998-2002, 2006-2012), Indian Institute of Science (2002-04), University of Guelph (2004-06). Until 2012, Dr. Rao held a permanent faculty position at the Indian Statistical Institute. He has won the Heiwa-Nakajima Award (Japan) and Fast Track Young Scientists Fellowship in Mathematical Sciences (DST, New Delhi). Dr. Rao also proved a major theorem in stationary population models, such as, Rao's Partition Theorem in Populations, Rao-Carey Theorem in stationary populations, and developed mathematical modeling-based policies for the spread of diseases like HIV, H5N1, COVID-19, etc. He developed a new set of network models for understanding avian pathogen biology on grid graphs (these were called chicken walk models), AI Models for COVID-19 and received wide coverage in the science media. Recently, he developed concepts such as “Exact Deep Learning Machines”, and “Multilevel Contours” within a bundle of Complex Number Planes.
Affiliations and expertise
Professor, Medical College of Georgia, USAVG
Venu Govindaraju
Dr. Venu Govindaraju, SUNY Distinguished Professor of Computer Science and Engineering, is the Vice President of Research and Economic Development of the University at Buffalo and founding director of the Center for Unified Biometrics and Sensors. He received his Bachelor’s degree with honors from the Indian Institute of Technology (IIT) in 1986, and his Ph.D. from UB in 1992. His research focus is on machine learning and pattern recognition in the domains of Document Image Analysis and Biometrics. Dr. Govindaraju has co-authored about 400 refereed scientific papers. His seminal work in handwriting recognition was at the core of the first handwritten address interpretation system used by the US Postal Service. He was also the prime technical lead responsible for technology transfer to the Postal Services in US, Australia, and UK. He has been a Principal or Co-Investigator of sponsored projects funded for about 65 million dollars. Dr. Govindaraju has supervised the dissertations of 30 doctoral students. He has served on the editorial boards of premier journals such as the IEEE Transactions on Pattern Analysis and Machine Intelligence and is currently the Editor-in-Chief of the IEEE Biometrics Council Compendium. Dr. Govindaraju is a Fellow of the ACM (Association of Computing Machinery), IEEE (Institute of Electrical and Electronics Engineers), AAAS (American Association for the Advancement of Science), the IAPR (International Association of Pattern Recognition), and the SPIE (International Society of Optics and Photonics). He is recipient of the 2004 MIT Global Indus Technovator award and the 2010 IEEE Technical Achievement award.
Affiliations and expertise
The State University of New York, Buffalo, NY, USACR
C.R. Rao
book “Ancient Inhabitants of Jebel Moya” published by the Cambridge Press under the joint authorship of Rao and two anthropologists. On the basis of work done at CU during the two year period, 1946-1948, Rao earned a Ph.D. degree and a few years later Sc.D. degree of CU and the rare honor of life fellowship of Kings College, Cambridge.
He retired from ISI in 1980 at the mandatory age of 60 after working for 40 years during which period he developed ISI as an international center for statistical education and research. He also took an active part in establishing state statistical bureaus to collect local statistics and transmitting them to Central Statistical Organization in New Delhi. Rao played a pivitol role in launching undergraduate and postgraduate courses at ISI. He is the author of 475 research publications and several breakthrough papers contributing to statistical theory and methodology for applications to problems in all areas of human endeavor. There are a number of classical statistical terms named after him, the most popular of which are Cramer-Rao inequality, Rao-Blackwellization, Rao’s Orthogonal arrays used in quality control, Rao’s score test, Rao’s Quadratic Entropy used in ecological work, Rao’s metric and distance which are incorporated in most statistical books.
He is the author of 10 books, of which two important books are, Linear Statistical Inference which is translated into German, Russian, Czec, Polish and Japanese languages,and Statistics and Truth which is translated into, French, German, Japanese, Mainland Chinese, Taiwan Chinese, Turkish and Korean languages.
He directed the research work of 50 students for the Ph.D. degrees who in turn produced 500 Ph.D.’s. Rao received 38 hon. Doctorate degree from universities in 19 countries spanning 6 continents. He received the highest awards in statistics in USA,UK and India: National Medal of Science awarded by the president of USA, Indian National Medal of Science awarded by the Prime Minister of India and the Guy Medal in Gold awarded by the Royal Statistical Society, UK. Rao was a recipient of the first batch of Bhatnagar awards in 1959 for mathematical sciences and and numerous medals in India and abroad from Science Academies. He is a Fellow of Royal Society (FRS),UK, and member of National Academy of Sciences, USA, Lithuania and Europe. In his honor a research Institute named as CRRAO ADVANCED INSTITUTE OF MATHEMATICS, STATISTICS AND COMPUTER SCIENCE was established in the campus of Hyderabad University.
Affiliations and expertise
University of Hyderabad Campus, IndiaRead Deep Learning on ScienceDirect