Computer
vision and image processing-based systems and their applications are already an
integral part of modern living and are expected to increase in prevalence and
complexity. Vision system provides the ability to handle and examine the large
data generated by cameras and make a decision based on the situational
requirement. As computational intelligent methods are especially adept at
rapidly resolving inexact situations or where there is incomplete knowledge,
they are being heavily researched and employed in this space. This merger
creates intelligent vision systems, which can be extremely versatile, and this book
focusses on the latest developments and current key research areas in the
field.
Key Features:
- Interdisciplinary approach to
intelligent computing applications for machine vision
- Encompasses high performance computing
for vision systems and control
- Includes present applications and
challenges for future development
- Reviews range of CI and ML
methodologies
- International author pool
Table of Contents:
Chapter 1: Drone based Vision System: Surveillance during Calamities
Chapter 2: Use of computer vision to inspect automatically machined workpieces
Chapter 3: Machine learning for vision based crowd management
Chapter 4: Skin cancer classification model based on hybrid deep feature generation and
iterative mRMR
Chapter 5: An analysis of human activity recognition systems and its importance in the
current era
Chapter 6: A Deep Learning Based Food Detection and Classification
Chapter 7: Detection of Images Recaptured Through Screenshot Based on Spatial Rich Model
Analysis
Chapter 8: Data augmentation for deep ensembles in polyp segmentation
Chapter 9: Identification of the onset of Parkinson’s disease through a multiscale classification
deep learning model utilizing a fusion of multiple conventional features with nDS-spatially exploited symmetrical convolutional pattern
Chapter 10: Computer Vision Approach With Deep Learning for Medical Intelligence System
Chapter 11: Machine Learning in medicine: Diagnosis of skin cancer using Support Vector
Machine (SVM) Classifier
About the Author :
Irshad Ahmad Ansari has been working as a faculty in
the discipline of Electronics and Communication Engineering, at Indian
Institute of Information Technology, Design and Manufacturing (IIITDM)
Jabalpur, India since 2017. He completed his PhD at IIT Roorkee and
subsequently joined Gwangju Institute of Science and Technology, South Korea as
a Postdoctoral fellow. His major research interest includes Image Processing,
Signal Processing, Soft Computing, Data Classification, Brain Computer
Interface.
Varun Bajaj (PhD, SMIEEE) is a faculty member at the
Electronics and Communication Engineering department at the Indian Institute of
Information Technology, Design and Manufacturing (IIITDM) Jabalpur. Prior to
this he worked as a visiting faculty in IIITDM Jabalpur and Assistant Professor
at Department of Electronics and Instrumentation, Shri Vaishnav Institute of
Technology and Science, Indore, India. He received B.E. degree in Electronics
and Communication Engineering from Rajiv Gandhi Technological University,
Bhopal, India in 2006, M.Tech. Degree with Honors in Microelectronics and VLSI
design from Shri Govindram Seksaria Institute of Technology & Science, Indore,
India in 2009. He received his Ph.D. degree in the Discipline of Electrical
Engineering, at Indian Institute of Technology Indore, India in 2014. He is an
Associate Editor of IEEE Sensor Journal and Subject Editor-in-Chief of IET
Electronics Letters. He also served as a Subject Editor of IET Electronics
Letters. He is Senior Member of the IEEE and also contributes as active
technical reviewer of leading International journals of IEEE, IET, and
Elsevier, etc. He has authored numerous research papers and edited several book
projects. His research interests include biomedical signal processing, image
processing, time frequency analysis, and computer-aided medical diagnosis.
