The book aims to provide a comprehensive exploration of the integration of machine learning and deep learning algorithms into the field of autonomous vehicles and advanced driver assistance systems. It also highlights the use of various sensing technologies such as LiDAR, radar, cameras, and ultrasonic sensors.
The book presents machine learning techniques relevant to autonomous systems, with a focus on deep learning, neural networks, and reinforcement learning, providing readers with a solid understanding of these foundational concepts. It further includes real-world applications, offering insights into how these cutting-edge techniques are being employed by industry leaders and startups to improve the perception capabilities of autonomous vehicles.
It is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer engineering, and automotive engineering.
Reihe
Sprache
Verlagsort
Verlagsgruppe
Zielgruppe
Für höhere Schule und Studium
Für Beruf und Forschung
Academic, Postgraduate, and Undergraduate Advanced
Illustrationen
74 s/w Zeichnungen, 22 s/w Tabellen, 83 s/w Abbildungen, 9 s/w Photographien bzw. Rasterbilder
22 Tables, black and white; 74 Line drawings, black and white; 9 Halftones, black and white; 83 Illustrations, black and white
Maße
Höhe: 234 mm
Breite: 156 mm
ISBN-13
978-1-032-85687-2 (9781032856872)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Dr. Meenakshi Malik is a distinguished academician and researcher in the field of Artificial Intelligence and Data Science. With over 12 years of experience in higher education, she currently serves as an Assistant Professor (III) in the Department of Computer Science and Engineering at BML Munjal University, Gurugram. A proud alumna of IIM Bangalore, Dr. Malik completed her Ph.D. in AI and Data Science from Maharshi Dayanand University, where her thesis-focused on analyzing driving behavior using big data-earned her the prestigious Best Ph.D. Thesis Award from the Honorable Vice President of India.
Her professional journey reflects a passion for teaching, mentorship, and research-driven innovation. Dr. Malik has published more than 40 papers in reputed SCI/SCIE/ESCI and Scopus-indexed journals and international conferences. She has authored several book chapters and is currently editing three academic books. With six patents to her credit, her work spans diverse applications in intelligent transportation systems, healthcare, cybersecurity, and smart devices.
She is actively guiding four Ph.D. scholars and regularly organizes faculty development programs, workshops, and student-centric research projects.
A certified IBM trainer and a Mendeley Advisor, she has also qualified multiple national-level examinations, including UGC-NET, HTET, and GATE. Her research interests include machine learning, big data analytics, driver behavior modeling, natural language processing, and AI for social good.
Dedicated to empowering future technologists, Dr. Meenakshi Malik continues to inspire innovation, critical thinking, and ethical AI development through her teaching, publications, and public engagements.
Prof. A.V. Senthil Kumar is working as a Professor and Director, PG and Research Department of Computer Applications, Hindusthan College of Arts & Science, Coimbatore, Tamilnadu. To his credit he has industrial experience for five years and teaching experience of 28 years. He has also received his Doctor of Science (D.Sc in Computer Science). He has to his credit 66 Book Chapters, 231 papers in International and National Journals, 77 papers in International Conferences in International and National Conferences, and edited 17 books and 3 Text books. He is as Associate Editor of IEEE Access. He is an Editor-in-Chief for many journals and Key Member for India, Machine Intelligence Research Lab (MIR Labs). He is an Editorial Board Member and Reviewer for various International Journals. He is also a Committee member for various International Conferences. He has guided 16 Ph.D scholars and guiding 4 Ph. D scholars now.
Alptekin Erkollar is a Professor of Management and Business Informatics and a member of the board of directors for ETCOP Europe. Dr. Erkollar, who was authorized signatory at the Union Bank of Switzerland (UBS), is a member of independent experts of European research and innovation for the European Commission, author of several books, and editorial board member of international journals.. Dr. Erkollar is editor of the international EBM series 'Enterprise and Business Management' and the MIT series 'Management, Processes and Information Technology'. His publications are available around the world.
Piotr Masloch is a Professor at Was Studies University in Warsaw, Management and Command Faculty. Prof. Piotr Masloch is an officer of the Polish Army and Dean's Representative for EU projects. He is an author and manager of international projects (founded by UE) in the field of new technologies and modern education. He is an active teacher and researcher in management, sustainable energy, sustainability and environmental impact. He is a reviewer of scientific publications of the best Polish Universities and international publishing houses,he is an author and co-author about 100 publications as a paper contribution on international journals, book chapters and conference proceedings. His research interest includes management, global aspects of management, globalization and new trends in management (AI, VR, MR).
Herausgeber*in
War Studies University, Poland
1. Introduction to Sensing Technologies and Artificial Intelligence in Mobility. 2. Sensing Technologies for Autonomous Vehicles. 3. The Power of Artificial Intelligence in Sensing. 4. Sensor Data Processing and Interpretation. 5. Safety and Reliability in Autonomous Vehicles. 6. Future of Sensing Technologies and Artificial Intelligence in Mobility. 7. Case Studies. 8. Challenges and Future Directions. 9. Conclusion.
