Advancement of Data Processing Methods for Artificial and Computing Intelligence (River Publishers Series in Computing and Information Science and Technology)
Author: Seema Rawat (Editor), V. Ajantha Devi (Editor), Praveen Kumar (Editor)
Publisher finelybook 出版社: River Publishers
Edition 版本: 1st
Publication Date 出版日期: 2024-04-26
Language 语言: English
Print Length 页数: 384 pages
ISBN-10: 8770040176
ISBN-13: 9788770040174
Book Description
This book emphasizes the applications of advances in data processing methods for Artificial Intelligence in today’s fast-changing world, as well as to serve society through research, innovation, and development in this field. This book is applicable to a wide range of data that contribute to data science concerns and can be used to promote research in this high-potential new field. People’s perceptions of the world and how they conduct their lives have changed dramatically as a result of technological advancements. The world has been gripped by technology, and the advances that are being made every day are undeniably transforming the planet. In the domains of Big Data, engineering, and data science, this cutting-edge technology is ready to support us.
Artificial intelligence (AI) is a current research topic because it can be applied to a wide range of applications and disciplines to solve complicated problems and find optimal solutions. In research, medicine, technology, and the social sciences, the benefits of AI have already been proven. Data science, also known as pattern analytics and mining, is a technique for extracting useful and relevant information from databases, enabling better decision-making and strategy formulation in a range of fields. As a result of the exponential growth of data in recent years, the combined notions of big data and AI have given rise to many study areas, such as scale-up behaviour from classical algorithms. Furthermore, combining numerous AI technologies from other areas (such as vision, security, control, and biology) in order to build efficient and durable systems that interact in the real world is a new problem. Despite recent improvements in fundamental AI technologies, the integration of these skills into larger, trustworthy, transparent, and maintainable systems is still in its development. Both conceptually and practically, there are a number of unanswered issues.
About the Author
Dr. Seema Rawat gained her Ph.D. in Computer Science in Engineering and currently she is working as Associate Professor in Amity University Tashkent, Uzbekistan. She has more than 16 year of experience in research, teaching and content writing. Her areas of interests include big data analytics, data mining, machine learning. etc. She has to her credit 12 Patents and has published more then 80+ research papers in international journals and conferences (Scopus Indexed). She is editor and reviewer for many books and conferences. She is First women to be part of the IP colloquium program of WIPO Switzerland Geneva and is an Active Member of WEC (Women Entrepreneurial Cell). She has been a panelist and speaker in many programs at corporate and university level. She has received the “Faculty Innovation Excellence Award 2019” on the occasion of the World Intellectual Property Day. The award was given by The Secretary of Department of Science & Technology (DST) Govt of India. She has also worked as Faculty Advisor of “AICSC (Amity IEEE Computer Society Chapter)” under AUSBI (Amity University Student Branch of IEEE). She is an Active member in IEEE, member of ACM, and member of IET(UK), SCIEI and other renowned technical societies.
Dr V. Ajantha Devi is working as a Research Head for AP3 Solutions, Chennai, Tamil Nadu, India. She received her Ph.D. from University of Madras in 2015, and has worked as Project Fellow under a UGC Major Research Project. She is a Senior Member of IEEE, and has been certified as “Microsoft Certified Application Developer” (MCAD) and “Microsoft Certified Technical Specialist” (MCTS) by Microsoft Corp. She has more than 40 papers in international journals and conference proceedings to her credit. She has written, co-authored, and edited a number of books in the field of computer science with international and national publishers like Elsevier, Springer, etc. She has been a member of the program committee/technical committee/chair/review board for a variety of international conferences. She has five Australian Patents and one Indian Patent to her credit in the areas of artificial intelligence, image processing and medical imaging. Her work in image processing, signal processing, pattern matching, and natural language processing is based on artificial intelligence, machine learning, and deep learning techniques. She has won many Best paper presentation awards as well as a few research-oriented international awards.
Dr. Praveen Kumar holds a doctorate and a master’s degree in computer science and engineering. He is currently employed at Amity University in Tashkent, Uzbekistan as an Associate Professor. He has over 15 years of teaching and research experience, and was acknowledged by the Government of West Bengal, India, as having the best Ph.D. thesis and as a Fellow Member of the Indian Institute of Machine Learning for excellent contributions to artificial intelligence and machine learning. Big data analytics, data mining, and machine learning are some of his areas of interest. He holds 9 patents/copyrights and has published over 100 research papers in international journals and conferences (all of which are Scopus-indexed). In the area of Big Data analytics and data mining, he is guiding 4 Ph.D. Research Scholars. He has given invited talks and guest lectures at Jamia Millia Islamia University, Delhi University’s Maharaja Agersen College, Vietnam’s Duy Tan University, and ECE Paris, France, among others. He is an active member of IEEE, a lifetime member of IETE, an ACM member, and a member of the IET (UK) and other prestigious technical organizations. He works with corporations and is the Technical Adviser for DeetyaSoft Pvt. Ltd. Noida, MyDigital360, and other companies.
