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This book presents high-quality research papers presented at Congress on Smart Computing Technologies (CSCT 2022) organized by SAU Center for Research and Innovative Learning (SCRIL), South Asian University, India, from 3–4 December 2022. The book extensively covers recent research in algorithms for smart computing, AI and machine learning in smart computing, edge computing algorithms, adversarial networks and autoencoders, data visualization, data mining, data analytics, machine learning, game theory, high-performance computing, mobile and ubiquitous platforms for smart environments,…mehr
This book presents high-quality research papers presented at Congress on Smart Computing Technologies (CSCT 2022) organized by SAU Center for Research and Innovative Learning (SCRIL), South Asian University, India, from 3–4 December 2022. The book extensively covers recent research in algorithms for smart computing, AI and machine learning in smart computing, edge computing algorithms, adversarial networks and autoencoders, data visualization, data mining, data analytics, machine learning, game theory, high-performance computing, mobile and ubiquitous platforms for smart environments, cloud/edge/fog computing technologies for smart systems, Internet of Things (IoT) and industrial IoT technologies for smart systems, smart device and hardware, security, privacy, and economics in smart environments, big data, healthcare informatics, smart precision agriculture, smart transportation, social network analysis, and human–computer interaction.
Dr. Jagdish Chand Bansal is an Associate Professor at South Asian University New Delhi and Visiting Faculty at Maths and Computer Science, Liverpool Hope University UK. Dr. Bansal obtained his Ph.D. in Mathematics from IIT Roorkee. Before joining SAU New Delhi he worked as an Assistant Professor at ABV- Indian Institute of Information Technology and Management Gwalior and BITS Pilani. His Primary area of interest is Swarm Intelligence and Nature Inspired Optimization Techniques. Recently, he proposed a fission-fusion social structure based optimization algorithm, Spider Monkey Optimization (SMO), which is being applied to various problems in the engineering domain. He has published more than 70 research papers in various international journals/conferences. He is the Section Editor (editor in chief) of the journal MethodsX published by Elsevier. He is the series editor of the book series Algorithms for Intelligent Systems (AIS) and Studies in Autonomic, Data-driven and Industrial Computing (SADIC) and Innovations in Sustainable Technologies and Computing (ISTC) published by Springer. He is also the Associate Editor of Engineering Applications of Artificial Intelligence (EAAI) and ARRAY published by Elsevier. He is the general secretary of the Soft Computing Research Society (SCRS). He has also received Gold Medal at UG and PG levels.
Harish Sharma is an associate professor in Department of Computer Science & Engineering at Rajasthan Technical University, Kota. He has worked at Vardhaman Mahaveer Open University, Kota, and Government Engineering College, Jhalawar. He received his B.Tech. and M.Tech. degrees in Computer Engg. from Govt. Engineering College, Kota, and Rajasthan Technical University, Kota, in 2003 and 2009, respectively. He obtained his Ph.D. from ABV-Indian Institute of Information Technology and Management, Gwalior, India. He is the secretary and one of the founder members of Soft Computing Research Society of India. He is a lifetime memberof Cryptology Research Society of India, ISI, Kolkata. He is an associate editor of “International Journal of Swarm Intelligence (IJSI)” published by Inderscience. He has also edited special issues of the many reputed journals like “Memetic Computing”, “Journal of Experimental and Theoretical Artificial Intelligence”, “Evolutionary Intelligence”, etc. His primary area of interest is nature-inspired optimization techniques. He has contributed in more than 105 papers published in various international journals and conferences.
Dr. Antorweep Chakravorty is an associate professor at the University of Stavanger. His current research and development work is in the field of applied blockchains, big data, large-scale machine learning, and data privacy. He has an interest in real-world problems, especially development of privacy-enabled data-driven services in smart energy, health care, and smart city domains. Antorweep completed his Ph.D. in 2015 with a thesis on privacy-preserving big data analytics at the University of Stavanger, Norway. Along with having a background in applied research in data-driven solutions, he is also involved in mentoring, teaching, and supervision.
Inhaltsangabe
1. Equity Market Price Prediction using Fuzzy-Genetic Machine Learning Algorithms.- 2. A Convolution Neural Network model to Classify Handwritten Digits from Skeletons.- 3. A Wavelet Thresholding-Based Approach for De-Noising the Color Image Affected by Gaussian Noise.- 4. Detection and classification of Diabetic Retinopathy using image processing and machine learning techniques.- 5. Analysis of EEG Signal of the Elderly for Hand Grip Muscle Activity.- 6. A systematic review of Image Fusion approaches.- 7. CASE STUDY: ANPR utilized for Smart Parking.- 8. Classification of Esophageal Cancer Using Ensembled CNN with Generalized Normal Distribution Optimization Model and Support Vector Machine Classifier.
1. Equity Market Price Prediction using Fuzzy-Genetic Machine Learning Algorithms.- 2. A Convolution Neural Network model to Classify Handwritten Digits from Skeletons.- 3. A Wavelet Thresholding-Based Approach for De-Noising the Color Image Affected by Gaussian Noise.- 4. Detection and classification of Diabetic Retinopathy using image processing and machine learning techniques.- 5. Analysis of EEG Signal of the Elderly for Hand Grip Muscle Activity.- 6. A systematic review of Image Fusion approaches.- 7. CASE STUDY: ANPR utilized for Smart Parking.- 8. Classification of Esophageal Cancer Using Ensembled CNN with Generalized Normal Distribution Optimization Model and Support Vector Machine Classifier.
1. Equity Market Price Prediction using Fuzzy-Genetic Machine Learning Algorithms.- 2. A Convolution Neural Network model to Classify Handwritten Digits from Skeletons.- 3. A Wavelet Thresholding-Based Approach for De-Noising the Color Image Affected by Gaussian Noise.- 4. Detection and classification of Diabetic Retinopathy using image processing and machine learning techniques.- 5. Analysis of EEG Signal of the Elderly for Hand Grip Muscle Activity.- 6. A systematic review of Image Fusion approaches.- 7. CASE STUDY: ANPR utilized for Smart Parking.- 8. Classification of Esophageal Cancer Using Ensembled CNN with Generalized Normal Distribution Optimization Model and Support Vector Machine Classifier.
1. Equity Market Price Prediction using Fuzzy-Genetic Machine Learning Algorithms.- 2. A Convolution Neural Network model to Classify Handwritten Digits from Skeletons.- 3. A Wavelet Thresholding-Based Approach for De-Noising the Color Image Affected by Gaussian Noise.- 4. Detection and classification of Diabetic Retinopathy using image processing and machine learning techniques.- 5. Analysis of EEG Signal of the Elderly for Hand Grip Muscle Activity.- 6. A systematic review of Image Fusion approaches.- 7. CASE STUDY: ANPR utilized for Smart Parking.- 8. Classification of Esophageal Cancer Using Ensembled CNN with Generalized Normal Distribution Optimization Model and Support Vector Machine Classifier.
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