1st Edition
Artificial Intelligence for Multimedia Information Processing Tools and Applications
Advances in artificial intelligence (AI), widespread mobile devices, internet technologies, multimedia data sources, and information processing have led to the emergence of multimedia processing. Multimedia processing is the application of signal processing tools to multimedia data—text, audio, images, and video—to allow the interpretation of these data, particularly in urban and smart city environments. This book discusses the new standards of multimedia and information processing from several technological perspectives, including analytics empowered by AI, streaming on the intelligent edge, multimedia edge caching and AI, services for edge AI, and hardware and devices for multimedia on edge intelligence.
FEATURES
- Covers a wide spectrum of enabling technologies for AI and machine learning for multimedia and information processing
- Includes many applications using AI, from robotics and driverless cars to environmental, human health, and remote sensing
- Presents an overview of the fundamentals of AI and multimedia processing: imaging, signal, and speech
- Explains new models and architectures for multimedia streaming, services, and caching for AI
- Discusses the emerging paradigms of the deployment of hardware and devices for multimedia on edge intelligence
- Gives recommendations for future research in multimedia and AI
This book is written for engineers and graduate students in image and signal processing, information processing, environmental engineering, medical and public health, etc., who are interested in machine learning, deep learning, and multimedia processing.
Section I: AI-Multimedia Information Processing
1. Monitoring Ancient Buildings Using UAV and Instant Image Segmentation Using Masked R-CNN
Sivasankari Jothiraj, Sridevi Balu, Neelaveni Rengarajan, and Nagarani Nagarajan
2. AI-Assisted Digital Forensics for Securing Industry 4.0 Assets
A. Shahela, Suchitra Gandu, B. Beulah Aswini, and Pramod Kumar Jha
3. State-of-the-Art Analysis in Reversible Data Hiding Techniques
R. Geetha and D. Kavitha
4. The Intelligent Research Laboratory: Artificial Intelligence/Machine Learning Methods for Chemists
Bhawani Narayan and Vinod Seshadri
Section II: AI and Its Applications in Public Health
5. MLACP 2.0: Utilizing Machine Learning to Predict Anticancer Peptide Activity from Protein Peptide Patterns
Sivakannan Subramani and A. Sharwin
6. An AI-Based Diagnostic System to Predict BI-RADS Scores for Detecting Breast Cancer over Mammograms
S. Ruban, Mohammed Jabeer, and Ram Shenoy Basti
7. Optimization Techniques and Their Applications in Prenatal Congenital Heart Defects: A Survey
D. Kavitha and R. Geetha
8. Analyzing Aortic Stenosis Diagnosis and Medication with Artificial Intelligence
Densil Raj V. Francis and L. R. Aravind Babu
9. A Study of the Role of Artificial Intelligence in Monitoring Environmental and Health Issues in the Post-COVID-19 Pandemic Era for Sustainable Living
Mahua Basu and Mausumi Das Nath
10. Cerebral Palsy Detection Using Vision Impairment and Machine Learning
S. Beatrice, J. Stella, and John Rose, S.J.
11. ECG-Based Diagnosis of Sudden Cardiac Death Using Machine Learning
Lohith Ashwa, Sivakannan Subramani, and Xavier Savarimuthu, S.J.
Section III: AI and Its Applications in Environmental Science
12. AI in Environmental Applications
Prasenjeet Acharjee
13. Automation of Adsorption Processes Using AI: Recent Trends and Prospects
Saizel Pathania, S. Daksa, Sanjanavhas Srinivasan, and Xavier Savarimuthu, S.J.
14. Application of Machine Learning Algorithms in the Field of Bioacoustics
Fiona Ghosh, Niranjana Nair, Pranav Elayadam, and Xavier Savarimuthu, S.J.
Section IV: AI and Its Applications in the Automobile Industry
15. Driverless Car Using AI
Prasenjeet Acharjee
Section V: AI and Computer Vision
16. Comparative Analysis of Feature-Based Image Stitching Algorithms
Pawni Gupta, Namratha Betala, and Sivakannan Subramani
Section VI: AI and Its Applications in Material Science
17. Revolutionizing Concrete Engineering: Predicting Material Properties with AI Insights
Khushi Sabarad and Sivakannan Subramani
Biography
Xavier Savarimuthu, S.J., is the Principal of St. Xavier’s College Jaipur, Rajasthan, India. He has spent more than two decades in the fields of scientific research, teaching, research, and consultancy in Jesuit higher education institutions like St. Xavier’s College (Vice Principal), Kolkata, and St. Joseph’s University (Research Director) in Bengaluru. He has taught at Santa Clara University, California, and Saint Joseph’s University, Philadelphia, where he held the endowed Donald MacLean Jesuit Chair. Dr. Savarimuthu’s academic prowess is reflected in the fact that he was a research assistant and a Fogarty trainee in the University of California, Berkeley’s Arsenic Research Program for his doctoral research. He was invited to deliver lectures in Stockholm (Sweden) and Manila (the Philippines). A few more feathers in his cap were added when he delivered invited lectures at the University of Oxford and at the United Nations climate summits while attending the famous COP 21 in Paris (France) and COP 23 in Bonn (Germany). He has presented and published extensively on arsenic pollution in West Bengal, both in India and abroad. His latest article, "The Earth We Want Requires Reconciliation", was published in four languages: French, Spanish, Latin, and English. He has authored a Cambridge University Press textbook titled Fundamentals of Environmental Studies. His second edited volume is Go Green for Sustainability, published by CRC Press/Taylor & Francis Group in Boca Raton, Florida, and Oxford, UK. Artificial Intelligence for Multimedia Information Processing: Tools and Applications is his third book in his lifetime achievement of focusing on current pertinent issues.
Sivakannan Subramani is Assistant Professor at St. Joseph’s University, Bangalore. He earned a PhD in medical image processing at the Medical Image Processing Laboratory, Department of Electronics and Instrumentation Engineering, Annamalai University, India, in 2018. He earned a master’s of engineering and a bachelor’s of engineering at Anna University, Chennai. His primary interests are medical image processing, deep learning, machine learning, data analytics, and ASIC/FPGA. He has more than ten years of academic and seven years of research experience, primarily working on predictive analytics and deep learning, with a main focus on solving real-life problems. He has completed public-funded research projects for the Indian Space Research Organization (ISRO), Defense Research and Development Organization (DRDO), and other client projects as project co-investigator. He has published research articles in various international journals and presented his research at several international conferences. He is a reviewer for several international scientific journals and a member of the Data Science Foundation, Data Science Association, Institute of Electrical and Electronics Engineers, and Institute of Electronics and Telecommunication Engineers, among others.
Alex Noel Joseph Raj earned a BE in electrical engineering at Madras University, India, in 2001, an ME in applied electronics at Anna University in 2005, and a PhD in engineering at the University of Warwick, Coventry, UK, in 2009. From October 2009 to September 2011, he was with Valeport Ltd Totnes, UK, as a design engineer. From March 2013 to March 2017, he was with the Department of Embedded Technology, School of Electronics Engineering, VIT University, Vellore, India, as a professor. Since March 2017, he has been with the Department of Electronic Engineering, College of Engineering, Shantou University, China. His research interests include machine learning, signal and image processing, and FPGA implementations. He specializes in image processing and has industrial and teaching experience in machine learning, deep networks signal and medical image processing, FPGA system design, MATLAB®, Simulink, machine vision systems, sonar systems, and embedded systems. He is constantly looking for dynamic interns and postdocs to join his research team at Shantou University China. His major technical skills are VHDL, MATLAB®, Simulink, C and Embedded C. He has published research articles in various international journals and has presented his research at several international conferences.