Intelligent Learning for Computer Vision (eBook, PDF)

Proceedings of Congress on Intelligent Systems 2020

• Format: PDF

Produktbeschreibung

This book is a collection of selected papers presented at the First Congress on Intelligent Systems (CIS 2020), held in New Delhi, India, during September 5–6, 2020. It includes novel and innovative work from experts, practitioners, scientists, and decision-makers from academia and industry. It covers selected papers in the area of computer vision. This book covers new tools and technologies in some of the important areas of medical science like histopathological image analysis, cancer taxonomy, use of deep learning architecture in dental care, and many more. Furthermore, this book reviews and discusses the use of intelligent learning-based algorithms for increasing the productivity in agricultural domain.

Produktdetails

• Verlag: Springer Singapore
• Erscheinungstermin: 19. Mai 2021
• Englisch
• ISBN-13: 9789813345829
• Artikelnr.: 61914518

Autorenporträt

Harish Sharma is Associate Professor at Rajasthan Technical University, Kota, in the Department of Computer Science & Engineering. He has worked at Vardhaman Mahaveer Open University Kota and Government Engineering College Jhalawar. He received his B.Tech. and M.Tech. degree in Computer Engineering from Government of 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 Secretary and one of the founder members of Soft Computing Research Society of India. He is a lifetime member of Cryptology Research Society of India, ISI, Kolkata. He is 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”, and “Evolutionary Intelligence”. Hisprimary area of interest is nature-inspired optimization techniques. He has contributed to more than 65 papers published in various international journals and conferences. Dr. Mukesh Saraswat is Associate Professor at Jaypee Institute of Information Technology, Noida, India. Dr. Saraswat has obtained his Ph.D. in Computer Science & Engineering from ABV-IIITM Gwalior, India. He has more than 18 years of teaching and research experience. He has guided 02 Ph.D. students, more than 50 M.Tech. and B.Tech. dissertations, and presently guiding 05 Ph.D. students. He has published more than 40 journal and conference papers in the area of image processing, pattern recognition, data mining, and soft computing. He was the part of successfully completed DRDE funded project on image analysis and currently running two projects funded by SERB-DST (New Delhi) on Histopathological Image Analysis and Collaborative Research Scheme (CRS), under TEQIP III (RTU-ATU) on Smile. He has been an active member of many organizing committees of various conferences and workshops. He was also Guest Editor of the Journal of Swarm Intelligence. He is an active member of IEEE, ACM, and CSI Professional Bodies. His research areas include image processing, pattern recognition, mining, and soft computing. Dr. Sandeep Kumar is currently Assistant Professor of Computer Science & Engineering at Amity University Rajasthan, Jaipur, India. Dr. Kumar holds a Ph.D. degree in Computer Science & Engineering, M.Tech. degree from RTU, Kota, and B.E. degree from Engineering College, Kota. Dr. Kumar was Assistant Professor of Computer Science & Engineering at ACEIT, Jaipur, 2008–2011, and Assistant Professor of Computer Science, Faculty of Engineering & Technology, Jagannath University, Jaipur, 2011–2017. Dr. Kumar was the head of computer science at Jagannath University, 2013–2017. He is also working as Guest Editor for many journals including International Journal of Intelligent Information and Database Systems (IJIIDS), International Journal of Agricultural Resources, Governance and Ecology (IJARGE), International Journal of Environment and Sustainable Development (IJESD), Inderscience, Recent Patents on Computer Science, and Bentham Science, member of editorial boards for many international journals, and member of technical program committees of many conferences. He has organized eight conferences as Conference Chair, Organizing Chair, and Technical Program Chair. Dr. Kumar has over fifty publications in well-known SCI/SCOPUS indexed international journals and conferences. He has authored/edited four books in the area of computer science and edited two conference proceedings. His research interests include nature-inspired algorithms, swarm intelligence, soft computing, and computational intelligence. Dr. Jagdish Chand Bansal is Associate Professor at South Asian University New Delhi and Visiting Faculty at Maths and Computer Science, Liverpool Hope University UK. Dr. Bansal has obtained his Ph.D. in Mathematics from IIT Roorkee. Before joining SAU New Delhi, he has worked as Assistant Professor at ABV-Indian Institute of Information Technology and Management Gwalior and BITS Pilani. He is Series Editor of the book series Algorithms for Intelligent Systems (AIS) published by Springer. He is Editor-in-Chief of International Journal of Swarm Intelligence (IJSI) published by Inderscience. He is also Associate Editor of IEEE ACESSS published by IEEE. He is the steering committee member and General Chair of the annual conference series SocProS. He is General Secretary of Soft Computing Research Society (SCRS). 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 from engineering domain. He has published more than 70 research papers in various international journals/conferences. He has supervised Ph.D. theses from ABV-IIITM Gwalior and SAU New Delhi. He has also received Gold Medal at UG and PG levels.

Inhaltsangabe

Development of Inter-Ethnic Harmony Search Algorithm based on Inter-Ethnic Reconciliation.- A Low-Cost Embedded Computer Vision System for the Classification of Recyclable Objects.- An Optimal Feature Selection Approach based on IBBO for Histopathological Image Classification.- Accuracy Evaluation of Plant Leaf Disease Detection and Classification using GLCM and Multiclass SVM Classifier.- A Deep Learning Technique for Automatic Teeth Recognition in Dental Panoramic X-Ray Images Using Modified Palmer Notation System.- Detection of Parkinson’s disease from hand-drawn images using Deep Transfer Learning.- An Empirical Analysis of Hierarchical and Partition Based Clustering Techniques in Optic Disc Segmentation.- Multi Class Support Vector Machine Based Household Object Recognition System Using Features Supported by Point Cloud Library.- Initialization of MLP Parameters using Deep Belief Networks for Cancer Classification.- An Improved Inception Layer Based Convolutional Neural Network For Identifying Rice Leaf Diseases.- Design & Implementation of Traffic Sign Classifier Using Machine Learning Model.- Designing controller parameter of wind turbine emulator using artificial bee colony algorithm.- Text-Document Orientation Detection Using Convolutional Neural Networks.- A Deep Learning based Segregation of Housing Image data for Real Estate application.

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Development of Inter-Ethnic Harmony Search Algorithm based on Inter-Ethnic Reconciliation.- A Low-Cost Embedded Computer Vision System for the Classification of Recyclable Objects.- An Optimal Feature Selection Approach based on IBBO for Histopathological Image Classification.- Accuracy Evaluation of Plant Leaf Disease Detection and Classification using GLCM and Multiclass SVM Classifier.- A Deep Learning Technique for Automatic Teeth Recognition in Dental Panoramic X-Ray Images Using Modified Palmer Notation System.- Detection of Parkinson's disease from hand-drawn images using Deep Transfer Learning.- An Empirical Analysis of Hierarchical and Partition Based Clustering Techniques in Optic Disc Segmentation.- Multi Class Support Vector Machine Based Household Object Recognition System Using Features Supported by Point Cloud Library.- Initialization of MLP Parameters using Deep Belief Networks for Cancer Classification.- An Improved Inception Layer Based Convolutional Neural Network For Identifying Rice Leaf Diseases.- Design & Implementation of Traffic Sign Classifier Using Machine Learning Model.- Designing controller parameter of wind turbine emulator using artificial bee colony algorithm.- Text-Document Orientation Detection Using Convolutional Neural Networks.- A Deep Learning based Segregation of Housing Image data for Real Estate application.