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      2. Teknik och industri
      3. Teknik: allmänt

      Advances in Information and Communication Technology

      Proceedings of the 2nd International Conference ICTA 2023, Volume 2

      AvPhung Trung Nghia,Vu Duc Thai

      Häftad, Engelska, 2024

      Del 848 i serien Lecture Notes in Networks and Systems

      2 182 kr

      Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

      Beskrivning

      This book contains four keynote abstracts and 83 best peer-reviewed papers selected from the 179 submissions at the 2nd  International Conference on Advances in ICT (ICTA 2023), which share research results and practical applications in ICT research and education. Technological changes and digital transformation that have taken place over the past decade have had significant impacts on all economic and social sectors. Information and Communication Technology (ICT) in general and artificial intelligence (AI) in particular have driven socio-economic growth.The topics cover all ICT-related areas and their contributions to socio-economic development, focusing on the most advanced technologies, such as AI. Researchers and practitioners in academia and industry use the books as a valuable reference for their research activities, teaching, learning, and advancing current technologies.The Conference is hosted by Thai Nguyen University of Information and Communication Technology (ICTU).

      Produktinformation

      • Utgivningsdatum:2024-01-04
      • Mått:155 x 235 x 25 mm
      • Vikt:828 g
      • Format:Häftad
      • Språk:Engelska
      • Serie:Lecture Notes in Networks and Systems
      • Antal sidor:459
      • Förlag:Springer International Publishing AG
      • ISBN:9783031508172

      Utforska kategorier

      • Teknik: allmänt inom Naturvetenskap och teknik
      • Artificiell intelligens inom Data och IT

      Mer om författaren

      Assoc. Prof. Phung Trung Nghia received his Engineer degree in Electronics and Telecommunications from Hanoi University of Science and Technology (HUST) in 2002. He completed his Master of Science in Telecommunications from Vietnam National University, Hanoi (VNUH) in 2007 and his Ph.D. degree in Information Science from Japan Advanced Institute of Science and Technology (JAIST) in 2013. He was Dean of the Faculty of Electronics and Telecommunications and Head of Academic Affairs. He has been ICTU's Rector. He received the Award for Excellent Young Researcher (Golden Globe Award) from Vietnam's Ministry of Science and Technology (MOST) in 2008. His main research interest lies in the interaction between signal processing and machine learning, and he has published more than 70 research papers related to this field. Dr. Vu Duc Thai got a Master of Science in Computer Science from Thai Nguyen University and a Ph.D. degree in Mathematical Foundationsfor Computers and Computing Systems from the Institute of Information Technology—Vietnam Academy of Science and Technology in 2012. He has been ICTU's Vice-Rector. His research relates to databases, information systems, and embedded systems (Cellular Neural Networks, FPGA). He has published more than 40 articles, books, and book chapters. He is an Editor and Reviewer for some international journals. Prof. Nguyen Thanh Thuy received an Engineer degree in Computing in 1982 and a Ph.D. degree in Computer Science from HUST in 1987. He was a Professor of computer science at HUST until 2011 and then at the VNU University of Engineering and Technology. Prof. Nguyen Thanh Thuy is now Head of the key laboratory for AI at the Faculty of Information Technology under VNU University of Engineering and Technology. His AI research interests are mainly in knowledge systems, soft computing, data mining, deep learning, hybrid intelligent systems, general AI, and responsible AI. Prof. Nguyen Thanh Thuy is now President of the National Committee for Professorships of Vietnam in Computer Science (upon Ministry of Education and Training), period 2018–2023. Assoc. Prof. Le Hoang Son is Vice-Director of VNU Information Technology Institute at Vietnam National University, Hanoi. His main research areas include soft computing foundation, knowledge-based systems, integrated machine learning for multimedia intelligence, and multi-modal and environmental AI, with an interest in healthcare and telecommunications network applications. Some applications have been deployed recently with software copyrights, such as a medical imaging support system with a deep learning model and knowledge graph, semi-supervised systems in object detection on remote sensing images, large recommender system (Mega RS) with techniques to extract information on electronic medical records, the software analyzes facial expressions and supports dynamic decision-making. Dr. Son has been a Vietnam Government Office Consultant since 2019. Prof. Dr. Van-Nam Huynh received a Ph.D. degree in Mathematics from Vietnam Academy of Science and Technology in 1999. He is a Professor at the School of Knowledge Science, JAIST. Also, he serves as a Research Fellow at The University of Economics Ho Chi Minh City, Vietnam. He was a Visiting Professor at the National Electronics and Computer Technology Center (NECTEC), Thailand, in 2019, an Adjunct Professor at Chiang Mai University, Thailand, from 2015 to 2017, and a Part-time Lecturer at Tsukuba University, Japan, from 2011 to 2015. His research interests include AI and machine learning, decision analysis and management science, modeling and reasoning with uncertain knowledge, argumentation and multi-agent systems, and Kansei information processing and applications. He serves as Area Editor of the International Journal of Approximate Reasoning, Editor-in-Chief of the InternationalJournal of Knowledge and Systems Science, and Area Editor of the Journal Array.

      Innehållsförteckning

      • A combination of Active Learning and Deep Learning for improving breast cancer prediction.- A Novel Arm Bone Fracture Detection Using Deep Learning.- A systematic review of Artificial Intelligence in Geographic Information Systems.- Build an effective system for container code recognition.- Building an Efficient Retriever System with Limited Resources.- Deep Learning based Coconut Fruit Maturity Classification.- Enhanced prediction of mRNA subcellular localization using a novel ensemble learning and hybrid approach.
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