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    Deep Learning in Genome Mapping

Deep Learning in Genome Mapping

Soumya Ranjan Nayak
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      The book aims to develop methodologies, and throw light on empirical research advances 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.

      Format: Hardback CONTRIBUTORS: Soumya Ranjan Nayak EAN: 9781032833811 COUNTRY: United Kingdom PAGES: 218 WEIGHT: 453 g HEIGHT: 234 mm
      PUBLISHED BY: Taylor & Francis Ltd DATE PUBLISHED: 2026-03-05 CITY: GENRE: COMPUTERS / Data Science / Data Analytics, COMPUTERS / Data Science / Neural Networks, COMPUTERS / Data Science / Machine Learning, MEDICAL / Genetics, SCIENCE / Chemistry / Computational & Molecular Modeling WIDTH: 156 mm SPINE:

      Book Themes:

      Automatic control engineering, Information technology: general topics, Relational databases, Data mining, Computer architecture and logic design, Neural networks and fuzzy systems

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      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 Universit

      The book aims to develop methodologies, and throw light on empirical research advances 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.

      Format: Hardback CONTRIBUTORS: Soumya Ranjan Nayak EAN: 9781032833811 COUNTRY: United Kingdom PAGES: 218 WEIGHT: 453 g HEIGHT: 234 mm
      PUBLISHED BY: Taylor & Francis Ltd DATE PUBLISHED: 2026-03-05 CITY: GENRE: COMPUTERS / Data Science / Data Analytics, COMPUTERS / Data Science / Neural Networks, COMPUTERS / Data Science / Machine Learning, MEDICAL / Genetics, SCIENCE / Chemistry / Computational & Molecular Modeling WIDTH: 156 mm SPINE:

      Book Themes:

      Automatic control engineering, Information technology: general topics, Relational databases, Data mining, Computer architecture and logic design, Neural networks and fuzzy systems

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      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 Universit

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