Stanimirovic / Stanimirovic / Zhang 6th EAI International Conference on Robotic Sensor Networks

1. Auflage 2023
ISBN: 978-3-031-33826-7
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 106 Seiten, eBook

Reihe: EAI/Springer Innovations in Communication and Computing

This book presents the proceedings of the 6th EAI International Conference on Robotics and Networks 2022 (ROSENET 2022). The conference explores the integration of networks and robotic technologies, which has become a topic of increasing interest for both researchers and developers from academic fields and industries worldwide. The authors posit that big networks will be the main approach to the next generation of robotic research, with the explosive number of networks models and increasing computational power of computers significantly extending the number of potential applications for robotic technologies while also bringing new challenges to the networking community. The conference provided a platform for researchers to share up-to-date scientific achievements in this field. The conference took place at Swansea University, Wales, Great Britain.

Zielgruppe

Research

Autoren/Hrsg.

Stanimirovic, Predrag S.

Zhang, Yudong

Xiao, Dunhui

Cao, Xinwei

Inhaltsverzeichnis

Chapter 1. An Intelligent Learning System based on Robotino Mobile Robot Platform.- Chapter 2. A Neocognitron Based on Multi-Objective Optimization for Few-Shot Learning.- Chapter 3. Milk temperature control system of calf feeding robot based on fuzzy PID.- Chapter 4. Bluff: A Multi-Robot Dispersion based on Hybrid Reciprocal Velocity Obstacles to solve the Blind Man’s Buff problem.- Chapter 5. Factors Influencing the Adoption of Robo Advisory Services: A UnifiedTheory of Acceptance and Use of Technology (UTAUT) Model Approach.- Chapter 6. A multi-region feature extraction and fusion strategy based CNN-Attention network for facial expression recognition.- Chapter 7. Real Time Surgical Instrument Object Detection using Yolov7.- Chapter 8. A Lightweight Blockchain Framework for Visual Homing and Navigation Robots.

Über Autor(innen)

Dr. Predrag S. Stanimirovic received the Ph.D. degree from the Faculty of Philosophy, University of Niš, Niš, Serbia, in 1996. He is currently working as a Full Professor with the Department of Computer Science, Faculty of Sciences and Mathematics, University of Niš. He has authored over 260 publications in various scientific journals, including six research monographs. His current research interests include research encompasses diverse fields of mathematics, applied mathematics, and computer science, which span multiple branches of numerical linear algebra, recurrent neural networks, symbolic computation, and operations research.  Dr. Yudong Zhang is a professor at the School of Computing and Mathematical Sciences, University of Leicester, UK. His research interests include deep learning and medical image analysis. He is the Fellow of IET, Fellow of EAI, and Fellow of BCS. He is the Senior Member of IEEE, IES, and ACM. He is the Distinguished Speaker of ACM. He was the 2019 & 2021 recipient of Clarivate Highly Cited Researcher. He has (co)authored over 400 peer-reviewed articles. There are more than 50 ESI Highly Cited Papers and 5 ESI Hot Papers in his (co)authored publications. His citation reached 22817 in Google Scholar (h-index 84). He has conducted many successful industrial projects and academic grants from NIH, Royal Society, GCRF, EPSRC, MRC, Hope, British Council, and NSFC. He has served as (Co-)Chair for more than 60 international conferences and workshops (including more than 10 IEEE or ACM conferences). More than 50 news presses have reported his research outputs, such as Reuters, BBC, Telegraph, Physics World, UK Today News, etc.Dr. Dunhui Xiao is a professor at Tongji University (Shanghai, China). He obtained his PhD from Imperial College London where he did his Post-doc.  His research interests include numerical modelling with a focus on non-intrusive reduced-order modellingof Navier-Stokes equations, fluid-structure interactions, and multiphase flows in porous media. He is also interested in data-driven modelling, data science, physical data combined machine learning and optimisation. He is a PI of a number of grants including EPSRC. He sits on the editorial boards for a number of journals and he is the reviewer for many journals and the EPSRC grants.  Dr. Xinwei Cao received the bachelor's degree from Shandong University, Jinan, China, 2009, the master's degree from Tongji University, Shanghai, China, in 2012, and the Ph.D. degree from Fudan University, Shanghai, China, in 2017, all in management. She is currently a full Professor with Jiangnan University, Wuxi, China. Her research interests include operations research, operational management, computational and quantitative finance, empirical asset pricing, and financial market.