Deep Learning Networks

ISBN-13: 9783031392436 / Twarda / 2023 / 226 str.

Azad M. Madni

Spis treści

Introduction.- Deep Learning.- Brief survey on Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL).- Tool Set for Deep Learning Applications.- Data-Set Design and Data Labeling.- DL Model: Design and Development.- Training and Testing of DL Model.- Deploying DL in Jetson Nano.- Deploying DL in Android Phone.- Deploying DL in Ultra96-V2 Field Programmable Gate Array (FPGA).- Conclusion.

O autorze

Dr. Jayakumar Singaram is a veteran in semiconductor electronics, and a Strategic consultant to companies, such as Mistral Solutions, Bangalore, Bilva infra, Bangalore, SunPlus Software, Bangalore, and Apollo Tyre's, Chennai, among others. He drives deployment ready solutions using AI in IoT Edge/Node. He began his career working in Hindustan Aeronautics Bangalore, followed by Cranes InfoTech and Mistral Solution before launching a start-up world by steering brands like Epigon Media Technologies, Rinanu Semiconductor, and many more. He had been one of the core team members and also led the design and development of `Networked Karaoke Machine'' (which enabled TAITO Corp. Japan to become No. 2 in the world of Networked Karaoke). Another major milestone has been his contribution to the development of Satellite Radio Receiver going by the brand name of ‘WorldSpace’. He is working on Deep Learning applications by using IBM Watson services. He has worked on key projects such as design and development of the Karaoke Machine (a project in collaboration with Analog Devices and MIT Media Lab) for TAITO Corp. He also worked on Satellite Radio Receiver for WorldSpace broadcast Satellites (and DAB Radio Receivers), by using low-cost Digital Signal Processors from Analog Devices. He has a B.Tech in Aeronautical engineering from Madras Institute of Technology and also holds an undergraduate degree in Mathematics from Madras University. He  has Masters and Doctorate degree  in Systems and Control Engineering from Indian Institute of Technology, Bombay and a Research Fellow at KU Leuven University.  As a Doctoral Thesis problem, he had worked on “ Simultaneous Stabilization of Feedback Systems”. He had worked as a Board Member and Dean of School of Computing Science and Engineering at Periyar Maniammai Institute of Science and Technology, Thanjavur, India, from 2007 to 2014. He was trustee of School of Music and Dance, Indiranagar-Bangalore, during 2009 to 2016. Link   www.jkuse.com provides more details about him. He would like to thank  the founders of Mistral Solutions,   Anees Ahmed and  Rajeev Ramachandra. And also he likes to thank  his family members, Dr Suneetha Rao, Dr Vaidhehi and Niranjan Kumar for their support while writing this early version of book.

Dr. S.S. Iyengar is currently the Distinguished University Professor, Founding Director of the Discovery Lab and Director of the US Army funded Center of Excellence in Digital Forensics at Florida International University, Miami. He is also the Distinguished Chaired Professor (Hon.) at National Forensics Sciences University, Gandhinagar, India. He has been involved with research and education in high-performance intelligent systems, Data Science and Machine Learning Algorithms, Sensor Fusion, Data Mining, and Intelligent Systems. Since receiving his Ph.D. degree in 1974 from MSU, USA, he has directed over 65 Ph.D. students, 100 Master’s students, and many undergraduate students who are now faculty at Major Universities worldwide or Scientists or Engineers at National Labs/Industries around the world. He has published more than 600 research papers, has authored/co-authored and edited 26 books. His h-index is 65 with over 20,100 citations and is among the list of top 2% cited scholars of Stanford study this year. His books are published by MIT Press, John Wiley and Sons, CRC Press, Prentice Hall, Springer Verlag, IEEE Computer Society Press, etc. One of his books titled “Introduction to Parallel Algorithms” has been translated into Chinese. During the last thirty years Dr. Iyengar has brought in over 65 million dollars for research and education. More recently in Spring 2021, Dr. Iyengar in collaboration with HBCUs were awarded a $2.25 M funding for setting up a Digital Forensics Center of Excellence over a period of 5 years (2021-2026). He has been awarded the Lifetime Achievement Award for his contribution to the field of Digital Forensics on November 8, 2022, during the 7th INTERPOL DIGITAL FORENSICS EXPERT GROUP (DFEG) MEETING at National Forensics Sciences University, Gandhinagar, Gujarat, India. He has providing the students and faculty with a vision for active learning and collaboration at Jackson State University, Louisiana State University, Florida International University, and across the world. Dr. Iyengar’s career is a distinguished one, marked by his incredible record of success in groundbreaking research, inspirational teaching and excellence in community service. It is his consistent drive to fight for and promote the minority and underrepresented groups which is his passion. Dr. S.S. Iyengar is an interdisciplinary computational scientist of international repute who has been a pioneer in multiple fields. Marked by his incredible record of success in the areas of world-class research, superb teaching, and excellence in community service, he has also significantly impacted industry, through his many discoveries and patents. His distinguished international and national research work have consistently been recognized by US government agencies, industry pioneers, and his research colleagues. His work has been featured on the cover of the National Science Foundation’s breakthrough technologies in both 2014 and again in 2016. Dr. Iyengar has garnered multiple awards for his work and made fundamental contributions in a variety of areas that impact our lives today. His seminal contributions continue to be seen in places like Raytheon, Telcordia, Motorola the United States Navy, DARPA and other universities and research laboratories around the world.

Dr. Azad Madni is the founder and CEO of Intelligent Systems Technology, Inc. a high tech company specializing in modeling and simulation technology for complex systems engineering, education and training. He's the Executive Director of University of Southern California's Systems Architecting and Engineering (SAE) Program and Professor of Astronautical Engineering in USC's Viterbi School of Engineering. His previous positions include Executive Vice President and Chief Technology Officer of Perceptronics, and Simulation Research Leader at Rockwell International on NASA's Space Shuttle Program. He pioneered the meta-discipline of transdisciplinary systems engineering to exploit the convergence of systems engineering with other disciplines. He is the creator of model-driven storytelling, a transdisciplinary approach that integrates model-based engineering with interactive storytelling in virtual worlds to enhance stakeholder participation in upfront engineering. His areas of expertise include model-based methods for architecting and design of resilient systems and enterprizes and intelligent systems for planning, decision making, training and tutoring. His research in these areas has been sponsored by the federal government, aerospace and automotive companies, several DOD agencies, Air Force, Army, Navy and Marine Corps. His research sponsors in the government include DARPA, OSD, DHS, S&T, MDA, DOE, NIST and NASA. His research sponsors in the aerospace and automotive industries include Boeing, General Motors, NGC, Raytheon, Hughes, Omnicon and SAIC. He has served as a consultant to Institute for Defense Analysis, RAND Corporation, UCLA, Oakridge National Laboratory, and Omnicon. Azad Madni's current research focuses on formal and probabilistic methods for complex systems engineering, model-based engineering frameworks and testbeds for defining, analyzing, integrating and testing of adaptive cyber-physical-human-systems, and system-of-systems and enterprize architecting. He is the co-founder and current chair of IEEE Systems, Man and Cybernetics, Model-Based Systems Engineering Technical Committee, and serves on the steering committees of multiple centers at USC. He received his B.S., M.S., and Ph.D. from the University of California, Los Angeles.

Blurb

This textbook presents multiple facets of design, development and deployment of deep learning networks for both students and industry practitioners. It introduces a deep learning tool set with deep learning concepts interwoven to enhance understanding. It also presents the design and technical aspects of programming along with a practical way to understand the relationships between programming and technology for a variety of applications. It offers a tutorial for the reader to learn wide-ranging conceptual modeling and programming tools that animate deep learning applications. The book is especially directed to students taking senior level undergraduate courses and to industry practitioners interested in learning about and applying deep learning methods to practical real-world problems. The unique features of this book are: 

• Easy-to-understand description of the multiple facets of design, development and deployment of deep learning networks;
• Practical tools that facilitate understanding of underlying technology;
• Covers wide-ranging conceptual modeling and programming tools that animate deep learning applications.