Overview
The book comprehensively covers a wide range of evolutionary computer vision methods and applications, feature selection and extraction for training and classification, and metaheuristic algorithms in image processing. It further discusses optimized image segmentation, its analysis, pattern recognition, and object detection. Features: Discusses machine learning-based analytics such as GAN networks, autoencoders, computational imaging, and quantum computing Covers deep learning algorithms in computer vision Showcases novel solutions such as multi-resolution analysis in imaging processing, and metaheuristic algorithms for tackling challenges associated with image processing Highlight optimization problems such as image segmentation and minimized feature design vector Presents platform and simulation tools for image processing and segmentation The book aims to get the readers familiar with the fundamentals of computational intelligence as well as the recent advancements in related technologies like smart applications of digital images, and other enabling technologies from the context of image processing and computer vision. It further covers important topics such as image watermarking, steganography, morphological processing, and optimized image segmentation. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in fields including electrical engineering, electronics, communications engineering, and computer engineering.
Full Product Details
Author: Nitin Mittal (Chandigarh University, India) ,
Amit Kant Pandit (SMVDU, Jammu, India) ,
Mohamed Abouhawwash (Mansoura University, Egypt.) ,
Shubham Mahajan (SMVDU, Jammu, India)
Publisher: Taylor & Francis Ltd
Imprint: CRC Press
Weight: 0.453kg
ISBN: 9781032591872
ISBN 10: 1032591870
Pages: 326
Publication Date: 27 June 2025
Audience:
College/higher education
,
Tertiary & Higher Education
Format: Paperback
Publisher's Status: Forthcoming
Availability: Not yet available
This item is yet to be released. You can pre-order this item and we will dispatch it to you upon its release.
Author Information
Dr. Amit Kant Pandit is working as an Associate Professor and is Ex-Hod, DECE, in Shri Mata Vaishno Devi University (SMVDU), Katra (India). He is a Senior member of IEEE and MIR labs member and has 19 years of academic experience. Mohamed Abouhawwash received the BSc and MSc degrees in statistics and computer science from Mansoura University, Mansoura, Egypt, in 2005 and 2011, respectively. He finished his Ph.D. in Statistics and Computer Science, 2015, in a channel program between Michigan State University, USA, and Mansoura University, Egypt. He is at Computational Mathematics, Science, and Engineering (CMSE), Biomedical Engineering (BME) and Radiology, Institute for Quantitative Health Science & Engineering (IQ), Michigan State University, East Lansing, MI 48824, USA. He is an Assistant Professor with the Department of Mathematics, Faculty of Science, Mansoura University, Egypt. In 2018, Dr. Abouhawwash is a Visiting Scholar with the Department of Mathematics and Statistics, Faculty of Science, Thompson Rivers University, Kamloops, BC, Canada. His current research interests include evolutionary algorithms, machine learning, image reconstruction, and mathematical optimization. Dr. Abouhawwash was a recipient of the best master’s and Ph.D. thesis awards from Mansoura University in 2012 and 2018, respectively. Dr. Shubham Mahajan (Member, IEEE, ACM) received the B.Tech. degree from Baba Ghulam Shah Badshah University, the M.Tech. degree from Chandigarh University and Ph.D. degree with Shri Mata Vaishno Devi University (SMVDU), Katra, India. He is working as a Assistant Professor with Ajeenkya D Y Patil University, Pune. He has eight Indian, one Australian, one German Patent to his credit in the area of artificial intelligence and image processing. He has authored/coauthored more than 50 publications including peer-reviewed journals and conferences. His main research interests include image processing, video compression, image segmentation, fuzzy entropy, nature-inspired computing methods with applications in optimization, data mining, machine learning, robotics, and optical communication, and also received the ‘Best Research Paper Award’ from ICRIC 2019 (Springer, LNEE) and also received the Best Student Award-2019, IEEE Region-10 Travel Grant Award-2019, 2nd runner up prize in IEEE RAS HACKATHON-2019 (Bangladesh) and IEEE Student Early Researcher Conference Fund (SERCF-2020), Emerging Scientist Award-2021, and IEEE Signal Processing Society Professional Development Grant-2021. He was a Campus Ambassador for IEEE, IIT Bombay, Kanpur, Varanasi, Delhi and various MNC’s. He is constantly looking for collaboration opportunities with foreign professors and students.
