Mu / Yujie / Lu 4th EAI International Conference on Robotic Sensor Networks

1. Auflage 2021
ISBN: 978-3-030-70451-3
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 132 Seiten, eBook

Reihe: EAI/Springer Innovations in Communication and Computing

This book presents papers presented at the 4th EAI International Conference on Robotic Sensor Networks. The conference explored 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 explore how big networks are becoming the main tool for the next generation of robotic research, owing to the explosive number of networks models and the increased computational power of computers. The papers discuss how these trends significantly extend the number of potential applications for robotic technologies while also bringing new challenges to the networks’ communities. The 2nd EAI International Conference on Robotic Sensor Networks was held online on November 21-22, 2020.

Zielgruppe

Research

Autoren/Hrsg.

Mu, Shenglin

Yujie, Li

Lu, Huimin

Inhaltsverzeichnis

Introduction.- A Mobile Robotic System for Rescue and Surveillance in Indoor Environment.- Study on the Learning in Intelligent Control using Neural Networks based on Back-Propagation and Differential Evolution.- Word Sense Disambiguation Graph-Based and Knowledge Base.- GDP Carbon Emission Prediction Base on Grey Model and Neural Network.- Automatic optimization of YOLOV3 image classification and positioning based on particle swarm optimization algorithm.- Contour Mask and Matting Driven Face Image Generation.- Eye-interface System using Convolutional Neural Networks for People with Physical Disabilities.- Proposal of Omnidirectional Movable Positioning Plate Using T-shaped Omni Wheel.- A general pseudo-random number generator based on chaos.- A Light chaotic encryption algorithm for real-time video encryption.- Intelligent Analysis and Presentation of IOT Image Collection in Private Cloud.- Conclusion.

Über Autor(innen)

Shenglin Mu received his B.E. degree in Mechanical Engineering and Automation in 2007 from the Northeastern University, China, and his M.E. and Ph.D. degrees in Electronic and Information Systems Engineering in 2010 and 2013, respectively, from the Yamaguchi University, Japan. In 2013, he joined the Department of Electronic Control Engineering, National Institution of Technology, Hiroshima College. In 2017, he joined the Graduate School of Science and Engineering, Ehime University. His current research interests include control engineering, especially intelligent control, intelligent algorithms, mechatronics, robotics, and sensing technology. Yujie Li received the B.S. degree in Computer Science and Technology from Yangzhou University in 2009. She received M.S. degrees in Electrical Engineering from Kyushu Institute of Technology and Yangzhou University in 2012, respectively. She received a Ph.D. degree from Kyushu Institute of Technology in 2015. Currently, she is an Assistant Professor at Fukuoka University in Japan. Her research interests include computer vision, sensors, and image segmentation. Huimin Lu received a B.S. degree in Electronics Information Science and Technology from Yangzhou University in 2008. He received M.S. degrees in Electrical Engineering from Kyushu Institute of Technology and Yangzhou University in 2011. He received a Ph.D. degree in Electrical Engineering from Kyushu Institute of Technology in 2014. From 2013 to 2016, he was a JSPS research fellow at Kyushu Institute of Technology. Currently, he joins in Kyushu Institute of Technology in Japan. His research interests include computer vision, robotics, artificial intelligence, and ocean observing.