Robotics, Control and Computer Vision

Select Proceedings of ICRCCV 2022
2023
ISBN: 978-981-99-0238-5
Verlag: Springer

Buch, Englisch, Band 1009, 620 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 943 g

Reihe: Lecture Notes in Electrical Engineering

This book presents select peer-reviewed papers from the International Conference on Robotics, Control, and Computer Vision (ICRCCV 2022). The contents focus on the latest research in the field of Robotics, their control, and computer vision in the context of robotics. The contributed papers have been arranged to give a flow to the reader. This book will be useful for students, researchers, and professionals from multidisciplinary fields such as mechanical engineering, electronics engineering, electrical engineering, computer science, and mathematics.

Zielgruppe

Research

Autoren/Hrsg.

Muthusamy, Hariharan

Botzheim, János

Nayak, Richi

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision
• Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung
• Technische Wissenschaften Technik Allgemein Mess- und Automatisierungstechnik
• Mathematik | Informatik EDV | Informatik Angewandte Informatik

Inhaltsverzeichnis

Chapter 1: Challenges and Opportunity for Salient Object Detection in COVID-19 Era: A Study.- Chapter 2: Multi-agent Task Assignment Using Swap-Based Particle Swarm Optimization for Surveillance and Disaster Management.- Chapter 3: Facemask Detection and Maintaining Safe Distance Using AI and ML to Prevent COVID-19—A Study.

Über Autor(innen)

Hariharan Muthusamy received a Ph.D. in Mechatronic Engineering (2010) from the University of Malaysia Perlis (UniMAP), Malaysia, a Master of Engineering in Applied Electronics (2006) from the Government College of Technology, India, and a Bachelor of Engineering in Electrical and Electronics Engineering (2002) from Government College of Technology (Affiliated to Bharathiar University), India. He is an Associate Professor in the Department of Electronics Engineering, National Institute of Technology Uttarakhand, India. He has published over 150 papers in refereed journals and conference proceedings. His major research interests include speech signal processing, biomedical signal and image processing, machine learning, deep learning, and optimization algorithms. He has supervised 9 Ph.D. and 4 Masters (research) students in the field of his expertise.

Jan’os Botzheim earned his M.Sc. and Ph.D. degrees from the Budapest University of Technology and Economics in 2001 and 2008, respectively. He joined the Department of Automation at Szechenyi Istvan University, Gyor, Hungary in 2007 as a senior lecturer, in 2008 as an assistant professor, and in 2009 as an associate professor. He was a visiting researcher at the Graduate School of System Design at the Tokyo Metropolitan University from September 2010 to March 2011 and from September 2011 to February 2012. He was an associate professor in the Graduate School of System Design at the Tokyo Metropolitan University from April 2012 to March 2017. He was an associate professor in the Department of Mechatronics, Optics, and Mechanical Engineering Informatics at the Budapest University of Technology and Economics from February 2018 to August 2021. He is the Head of the Department of Artificial Intelligence at Eötvös Loránd University, Faculty of Informatics, Budapest, Hungary, since September 2021. His research interest areas are computational intelligence, automatic identification of fuzzy rule-based models and some neural network models, bacterial evolutionary algorithms, memetic algorithms, applications of computational intelligence in robotics, and cognitive robotics. He has about 180 papers in journals and conference proceedings. Richi Nayak is the Leader of the Applied Data Science Program at the Centre for Data Science and a Professor of Computer science at Queensland University of Technology, Brisbane Australia. She has a driving passion to address pressing societal problems by innovating the Artificial Intelligence field underpinned by fundamental research in machine learning, data mining, and text mining. Her research has resulted in the development of novel solutions to address industry-specific problems in Marketing, K 12 Education, Agriculture, Digital Humanities, and Mining. She has made multiple advances in social media mining, deep neural networks, multi-view learning, matrix/tensor factorization, clustering, and recommender systems. She has authored over 180 high-quality refereed publications. Her research leadership is recognized by multiple best paper awards and nominations at international conferences, QUT Postgraduate Research Supervision awards, and the 2016 Women in Technology (WiT) Infotech Outstanding Achievement Award in Australia. She holds a Ph.D. in Computer Science from the Queensland University of Technology and a Master in Engineering from IIT Roorkee.