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.

Contents

1. Computer Vision
2. Challenges and Opportunity for Salient Object Detection in COVID-19 Era: A Study
3. Human Activity Recognition Using Deep Learning
4. Recovering Images Using Image inpainting Techniques
5. Literature Review for Automatic Detection and Classification of intracranial Brain Hemorrhage Using Computed Tomography Scans
6. A Pilot Study for Profiling Diabetic Foot Ulceration Using Machine Learning Techniques
7. A Deep Learning Approach for Gaussian Noise-Level Quantification
8. Performance Evaluation of Single Sample Ear Recognition Methods
9. Al-Based Real-Time Monitoring for Social Distancing Against COVID-19 Pandemic
10. Human Act ivity Recognition in Video Sequences Based on the Integration of Optical Flow and Appearance of Human Objects
11. Multi-agent Task Assignment Using Swap -Based Particle Swarm Optimization for Surveillance and Disaster Management
12. Facemask Detection and Maintaining Safe Distance Using Al and ML to Prevent COVID-1 9- A Study
13. A Machine Learning Framework for Breast Cancer Detection and Classification
14. Vision Transformers for Breast Cancer Classification from Thermal Images
15. An Improved Fourier Transformation Method for Single-Sample Ear Recognition
16. Driver Drowsiness Detection for Road Safety Using Deep Learning
17. Performance Evaluation of Different Machine Learning Models in Crop Selection
18. Apriori Based Medicine Recommendation System
19. NPIS: Number Plate Identification System
20. Leveraging Advanced Convolutional Neural Networks and Transfer Learning for Vision-Based Human Act ivity Recognition
21. Control Techniques and Their Applications
22. Real Power Loss Reduction by Chaotic Based Riodinidae Optimization Algorithm
23. SG Enabled lo T Based Automatic Industrial Plant Monitoring System
24. Criterion to Determine the Stability of Systems with Finite Wordlength and Delays Using Bessel- Legendre Inequalities
25. Adaptive Control for Stabilization of Ball and Beam System Using Hinfty Control
26. Optimal Robust Controller Design for a Reduced Model AVR System Using COM and FOPl11Dμ
27. Neural Network Based DSTATCOM Control for Power Quality Enhancement
28. An Extensive Critique on FACTS Controllers and Its Utilization in Micro Grid and Smart Grid Power Systems
29. Arctangent Framework Based Least Mean Square/Fourth Algorithm for System Identification
30. Robotics and Autonomous Vehicles
31. Stabilization of Ball Balancing Robots Using Hierarchical Sliding Mode Control with State-Dependent Switching Gain
32. Programmable Bot for Multi Terrain Environment
33. A Computer Vision Assisted Yoga Trainer for a Naive Performer by Using Human Joint Detection
34. Study of Deformation in Cold Rolled Al Sheets
35. Modelling and Control of Semi-automated Microfluidic Dispensing System
36. Im-SMART: Developing lmmersive Student Participation in the Classroom Augmented with Mobile Telepresence Robot
37. Architecture and Algorithms for a Pixhawk- Based Autonomous Vehicle
38. 30 Obstacle Detection and Path Planning for Aerial Platform Using Modified DWA Approach
39. Vibration Suppression of Hand Tremor Using Active Vibration Strategy: A Numerical Study
40. Design of a Self-reconfigurable Robot with Roll, Crawl, and Climb Features for False Ceiling Inspection Task
41. Smart Technologies for Mobility and Healthcare
42. Review Paper on Joint Beamforming, Power Control and Interference Coordination for Non-orthogonal Multiple Access in Wireless Communication Networks for Efficient Data Transmission
43. 30 Reconstruction Methods from Multi-aspect Tomo SAR Method: A Survey
44. Security and Privacy in loMT-Based Digital Health care: A Survey
45. SG Technology- Enabled loT System for Early Detection and Prevention of Contagious Diseases
46. A Brief Review of Current Smart Electric Mobility Facilities and Their Future Scope
47. Gold-ZnO Coated Surface Plasmon Resonance Refractive Index Sensor Based on Photonic Crystal Fiber with Tetra Core in Hexagonal Lattice of Elliptical Air Holes
48. Fault Detection and Diagnostics in a Cascaded Multilevel Inverter Using Artificial Neural Network
49. Identification of Multiple Solutions Using Two -Step Optimization Technique for Two -Level Voltage Source Inverter
50. A Review on Recent Trends in Charging Stations for Electric Vehicles
51.  IoT-Based Vehicle Charging Eco System for Smart Cities

About the Author

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.