Autorentext

Dr. Soumya Ranjan Nayak is an Assistant Professor at the School of Computer Engineering, KIIT University, Odisha, India. He holds a Ph.D. and M.Tech in Computer Science and Engineering under an MHRD fellowship and has over 150 publications, 16 book chapters, 6 books, and 9 patents (6 granted). His research interests include medical image analysis, machine learning, deep learning, and computer vision. With over 1500 citations, he has an h-index of 19 and i10-index of 46. Dr. Nayak serves as an associate editor and reviewer for several reputed journals and has contributed to numerous international conferences as a technical committee member.

Dr. Shailendra Pratap Singh is an Associate Professor in the Department of Computer Science and Engineering at Madan Mohan Malaviya University of Technology, Gorakhpur, India. With around 15 years of academic experience, he holds a Ph.D. from MNNIT Allahabad and specializes in Artificial Intelligence, IoT, Optimization, Algorithms, and Data Science. He has authored over 75 research papers in reputed journals and conferences, including Springer, Elsevier, and IEEE, and has edited multiple scholarly books. Known for his innovative teaching using design thinking, he also serves as a consultant in Industrial IoT and advisor to various start-ups and professional organizations.

Prof. Jagendra Singh, Senior Member of IEEE, is a Professor at the School of Computer Science Engineering and Technology, Bennett University, Greater Noida. With over 18 years of academic and research experience, he previously served at NIT Calicut. He earned his Ph.D. from Jawaharlal Nehru University, New Delhi, and completed his postdoctoral research at the Singapore Institute of Technology. Prof. Singh has published over 182 research papers, holds 50 patents, and authored 13 books. His key research areas include Natural Language Processing, Information Retrieval, Sentiment Analysis, Recommendation Systems, Deep Learning, Generative AI, and Data Analytics.

Dr. Prabhishek Singh, Senior Member of IEEE and ACM, is an Associate Professor at Bennett University, India, and Honorary Adjunct Faculty at Maryam Abacha American University of Nigeria. Recognized among the World's Top 2% Scientists (2024) by Stanford University & Elsevier, he holds a Ph.D. in Computer Science and has over nine years of academic and research experience. His expertise lies in image processing, computer vision, and deep learning. Dr. Singh has authored 210+ research papers and serves in editorial roles across leading SCI/SCIE/Scopus journals. He is also an active reviewer, editor, and guest editor for numerous reputed publications.

Prof. Manoj Diwakar is a Professor in the Department of Computer Science and Engineering at Graphic Era University, Dehradun, with 16 years of academic and industry experience. He holds a Ph.D. in Computer Science from Babasaheb Bhimrao Ambedkar University, Lucknow, and earned his M.Tech from MITS Gwalior. He has previously served at DIT University, Uttaranchal University, and Mody University. A Professional Member of IEEE and Life Member of IAENG, his research interests include image processing, information security, and medical imaging. Dr. Diwakar has authored around 250 research publications across reputed journals, conferences, books, and book chapters globally.

Prof. Deepak Garg, Ph.D. in Computer Science (Efficient Algorithm Design), is a distinguished academic with 25 years of experience. He is currently the Vice Chancellor of SR University, Warangal. He has served as Professor and Dean at Thapar Institute and Bennett University. A leading voice in Artificial Intelligence, he is on the Advisory Committee of AIRAWAT, India's Supercomputing Mission. He has contributed to NAAC, NBA, UGC, and AICTE, and serves on the tech advisory boards of Drishya.ai and ByteXL. India's only CAC ABET Commissioner, he has held leadership roles in IEEE societies, driving innovation in AI and computing education.

Klappentext

The book aims to develop methodologies and throw light on the advances in empirical research of various machine learning systems through data mining and parallel programming using GPU approaches. It reviews concepts of existing machine learning and deep learning techniques and how these can be implemented in GPU computing with CUDA architecture. The book also discusses modern machine learning techniques for effective big data management in accordance with worldwide standards in the field.

Covering diverse areas, this publication is meant for academicians, data scientists, industrial professionals, researchers and students interested in uncovering the latest innovations in the field.

Inhalt

Preface. Computation and Analysis for Genome Mapping using the Deep Learning-based Optimization Algorithm. Prediction for Genome Mapping with the Multi-objective Evolutionary Algorithm. Deep Learning and Medical Data Engineering for Knowledge Discovery. Integrating DL Techniques for Precise Genome Mapping: Methods and Applications. Analysing Genomes using Deep Learning and Image Processing Techniques. Introduction to Neural network and Machine Learning as a Subset of AI. Advancing Smart Healthcare: Enhanced Image Analysis and Feature Extraction through Integration of Sharpening Techniques and Edge Detection Algorithms. Optimizing Noise Reduction Strategies in Medical Imaging through Advanced Techniques and Performance Evaluation Metrics. Revolutionizing Medicine: Machine Learning Innovations in Medical Science. Development and Validation of an AI-Based Model for Heart Delineation in Chest X-Ray Images. Index.