Data Science For Nano Image Analysis

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Data Science for Nano Image Analysis

Author : Chiwoo Park
Publisher : Springer Nature
ISBN 13 : 3030728226
Total Pages : 376 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Data Science for Nano Image Analysis by : Chiwoo Park

Download or read book Data Science for Nano Image Analysis written by Chiwoo Park and published by Springer Nature. This book was released on 2021-07-31 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book combines two distinctive topics: data science/image analysis and materials science. The purpose of this book is to show what type of nano material problems can be better solved by which set of data science methods. The majority of material science research is thus far carried out by domain-specific experts in material engineering, chemistry/chemical engineering, and mechanical & aerospace engineering. The book could benefit materials scientists and manufacturing engineers who were not exposed to systematic data science training while in schools, or data scientists in computer science or statistics disciplines who want to work on material image problems or contribute to materials discovery and optimization. This book provides in-depth discussions of how data science and operations research methods can help and improve nano image analysis, automating the otherwise manual and time-consuming operations for material engineering and enhancing decision making for nano material exploration. A broad set of data science methods are covered, including the representations of images, shape analysis, image pattern analysis, and analysis of streaming images, change points detection, graphical methods, and real-time dynamic modeling and object tracking. The data science methods are described in the context of nano image applications, with specific material science case studies.

In-Situ Transmission Electron Microscopy Experiments

Author : Renu Sharma
Publisher : John Wiley & Sons
ISBN 13 : 3527347984
Total Pages : 389 pages
Book Rating : 4.5/5 (273 download)

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Book Synopsis In-Situ Transmission Electron Microscopy Experiments by : Renu Sharma

Download or read book In-Situ Transmission Electron Microscopy Experiments written by Renu Sharma and published by John Wiley & Sons. This book was released on 2023-05-15 with total page 389 pages. Available in PDF, EPUB and Kindle. Book excerpt: In-Situ Transmission Electron Microscopy Experiments Design and execute cutting-edge experiments with transmission electron microscopy using this essential guide In-situ microscopy is a recently-discovered and rapidly-developing approach to transmission electron microscopy (TEM) that allows for the study of atomic and/or molecular changes and processes while they are in progress. Experimental specimens are subjected to stimuli that replicate near real-world conditions and their effects are observed at a previously unprecedented scale. Though in-situ microscopy is becoming an increasingly important approach to TEM, there are no current texts combining an up-to-date overview of this cutting-edge set of techniques with the experience of in-situ TEM professionals. In-Situ Transmission Electron Microscopy Experiments meets this need with a work that synthesizes the collective experience of myriad collaborators. It constitutes a comprehensive guide for planning and performing in-situ TEM measurements, incorporating both fundamental principles and novel techniques. Its combination of technical detail and practical how-to advice makes it an indispensable introduction to this area of research. In-Situ Transmission Electron Microscopy Experiments readers will also find: Coverage of the entire experimental process, from method selection to experiment design to measurement and data analysis Detailed treatment of multimodal and correlative microscopy, data processing and machine learning, and more Discussion of future challenges and opportunities facing this field of research In-Situ Transmission Electron Microscopy Experiments is essential for graduate students, post-doctoral fellows, and early career researchers entering the field of in-situ TEM.

Handbook of Dynamic Data Driven Applications Systems

Author : Frederica Darema
Publisher : Springer Nature
ISBN 13 : 3031279867
Total Pages : 937 pages
Book Rating : 4.0/5 (312 download)

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Book Synopsis Handbook of Dynamic Data Driven Applications Systems by : Frederica Darema

Download or read book Handbook of Dynamic Data Driven Applications Systems written by Frederica Darema and published by Springer Nature. This book was released on 2023-10-16 with total page 937 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Second Volume in the series Handbook of Dynamic Data Driven Applications Systems (DDDAS) expands the scope of the methods and the application areas presented in the first Volume and aims to provide additional and extended content of the increasing set of science and engineering advances for new capabilities enabled through DDDAS. The methods and examples of breakthroughs presented in the book series capture the DDDAS paradigm and its scientific and technological impact and benefits. The DDDAS paradigm and the ensuing DDDAS-based frameworks for systems’ analysis and design have been shown to engender new and advanced capabilities for understanding, analysis, and management of engineered, natural, and societal systems (“applications systems”), and for the commensurate wide set of scientific and engineering fields and applications, as well as foundational areas. The DDDAS book series aims to be a reference source of many of the important research and development efforts conducted under the rubric of DDDAS, and to also inspire the broader communities of researchers and developers about the potential in their respective areas of interest, of the application and the exploitation of the DDDAS paradigm and the ensuing frameworks, through the examples and case studies presented, either within their own field or other fields of study. As in the first volume, the chapters in this book reflect research work conducted over the years starting in the 1990’s to the present. Here, the theory and application content are considered for: Foundational Methods Materials Systems Structural Systems Energy Systems Environmental Systems: Domain Assessment & Adverse Conditions/Wildfires Surveillance Systems Space Awareness Systems Healthcare Systems Decision Support Systems Cyber Security Systems Design of Computer Systems The readers of this book series will benefit from DDDAS theory advances such as object estimation, information fusion, and sensor management. The increased interest in Artificial Intelligence (AI), Machine Learning and Neural Networks (NN) provides opportunities for DDDAS-based methods to show the key role DDDAS plays in enabling AI capabilities; address challenges that ML-alone does not, and also show how ML in combination with DDDAS-based methods can deliver the advanced capabilities sought; likewise, infusion of DDDAS-like approaches in NN-methods strengthens such methods. Moreover, the “DDDAS-based Digital Twin” or “Dynamic Digital Twin”, goes beyond the traditional DT notion where the model and the physical system are viewed side-by-side in a static way, to a paradigm where the model dynamically interacts with the physical system through its instrumentation, (per the DDDAS feed-back control loop between model and instrumentation).

Data Science for Wind Energy

Author : Yu Ding
Publisher : CRC Press
ISBN 13 : 9780367729097
Total Pages : 0 pages
Book Rating : 4.7/5 (29 download)

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Book Synopsis Data Science for Wind Energy by : Yu Ding

Download or read book Data Science for Wind Energy written by Yu Ding and published by CRC Press. This book was released on 2020-12-18 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science for Wind Energy provides an in-depth discussion on how data science methods can improve decision making for wind energy applications, near-ground wind field analysis and forecast, turbine power curve fitting and performance analysis, turbine reliability assessment, and maintenance optimization for wind turbines and wind farms. A broad set of data science methods covered, including time series models, spatio-temporal analysis, kernel regression, decision trees, kNN, splines, Bayesian inference, and importance sampling. More importantly, the data science methods are described in the context of wind energy applications, with specific wind energy examples and case studies. Please also visit the author's book site at https://aml.engr.tamu.edu/book-dswe. Features Provides an integral treatment of data science methods and wind energy applications Includes specific demonstration of particular data science methods and their use in the context of addressing wind energy needs Presents real data, case studies and computer codes from wind energy research and industrial practice Covers material based on the author's ten plus years of academic research and insights

Materials Data Science

Author : Stefan Sandfeld
Publisher : Springer Nature
ISBN 13 : 3031465652
Total Pages : 629 pages
Book Rating : 4.0/5 (314 download)

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Book Synopsis Materials Data Science by : Stefan Sandfeld

Download or read book Materials Data Science written by Stefan Sandfeld and published by Springer Nature. This book was released on with total page 629 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Apply Data Science

Author : Thomas Barton
Publisher : Springer Nature
ISBN 13 : 365838798X
Total Pages : 234 pages
Book Rating : 4.6/5 (583 download)

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Book Synopsis Apply Data Science by : Thomas Barton

Download or read book Apply Data Science written by Thomas Barton and published by Springer Nature. This book was released on 2023-01-01 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers an introduction to the topic of data science based on the visual processing of data. It deals with ethical considerations in the digital transformation and presents a process framework for the evaluation of technologies. It also explains special features and findings on the failure of data science projects and presents recommendation systems in consideration of current developments. Machine learning functionality in business analytics tools is compared and the use of a process model for data science is shown.The integration of renewable energies using the example of photovoltaic systems, more efficient use of thermal energy, scientific literature evaluation, customer satisfaction in the automotive industry and a framework for the analysis of vehicle data serve as application examples for the concrete use of data science. The book offers important information that is just as relevant for practitioners as for students and teachers.

Statistical Methods for Materials Science

Author : Jeffrey P. Simmons
Publisher : CRC Press
ISBN 13 : 1498738214
Total Pages : 537 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Statistical Methods for Materials Science by : Jeffrey P. Simmons

Download or read book Statistical Methods for Materials Science written by Jeffrey P. Simmons and published by CRC Press. This book was released on 2019-02-13 with total page 537 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data analytics has become an integral part of materials science. This book provides the practical tools and fundamentals needed for researchers in materials science to understand how to analyze large datasets using statistical methods, especially inverse methods applied to microstructure characterization. It contains valuable guidance on essential topics such as denoising and data modeling. Additionally, the analysis and applications section addresses compressed sensing methods, stochastic models, extreme estimation, and approaches to pattern detection.

Handbook of Research on Deep Learning-Based Image Analysis Under Constrained and Unconstrained Environments

Author : Raj, Alex Noel Joseph
Publisher : IGI Global
ISBN 13 : 1799866920
Total Pages : 381 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Handbook of Research on Deep Learning-Based Image Analysis Under Constrained and Unconstrained Environments by : Raj, Alex Noel Joseph

Download or read book Handbook of Research on Deep Learning-Based Image Analysis Under Constrained and Unconstrained Environments written by Raj, Alex Noel Joseph and published by IGI Global. This book was released on 2020-12-25 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent advancements in imaging techniques and image analysis has broadened the horizons for their applications in various domains. Image analysis has become an influential technique in medical image analysis, optical character recognition, geology, remote sensing, and more. However, analysis of images under constrained and unconstrained environments require efficient representation of the data and complex models for accurate interpretation and classification of data. Deep learning methods, with their hierarchical/multilayered architecture, allow the systems to learn complex mathematical models to provide improved performance in the required task. The Handbook of Research on Deep Learning-Based Image Analysis Under Constrained and Unconstrained Environments provides a critical examination of the latest advancements, developments, methods, systems, futuristic approaches, and algorithms for image analysis and addresses its challenges. Highlighting concepts, methods, and tools including convolutional neural networks, edge enhancement, image segmentation, machine learning, and image processing, the book is an essential and comprehensive reference work for engineers, academicians, researchers, and students.

Intelligent Computing and Innovation on Data Science

Author : Sheng-Lung Peng
Publisher : Springer Nature
ISBN 13 : 9811631530
Total Pages : 590 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Intelligent Computing and Innovation on Data Science by : Sheng-Lung Peng

Download or read book Intelligent Computing and Innovation on Data Science written by Sheng-Lung Peng and published by Springer Nature. This book was released on 2021-09-27 with total page 590 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers high-quality papers presented at 2nd International Conference on Technology Innovation and Data Sciences (ICTIDS 2021), organized by Lincoln University, Malaysia from 19 – 20 February 2021. It covers wide range of recent technologies like artificial intelligence and machine learning, big data and data sciences, Internet of Things (IoT), and IoT-based digital ecosystem. The book brings together works from researchers, scientists, engineers, scholars and students in the areas of engineering and technology, and provides an opportunity for the dissemination of original research results, new ideas, research and development, practical experiments, which concentrate on both theory and practices, for the benefit of common man.

Artificial Intelligence, Machine Learning, and Data Science Technologies

Author : Neeraj Mohan
Publisher : CRC Press
ISBN 13 : 1000460525
Total Pages : 311 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Artificial Intelligence, Machine Learning, and Data Science Technologies by : Neeraj Mohan

Download or read book Artificial Intelligence, Machine Learning, and Data Science Technologies written by Neeraj Mohan and published by CRC Press. This book was released on 2021-10-11 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive, conceptual, and detailed overview of the wide range of applications of Artificial Intelligence, Machine Learning, and Data Science and how these technologies have an impact on various domains such as healthcare, business, industry, security, and how all countries around the world are feeling this impact. The book aims at low-cost solutions which could be implemented even in developing countries. It highlights the significant impact these technologies have on various industries and on us as humans. It provides a virtual picture of forthcoming better human life shadowed by the new technologies and their applications and discusses the impact Data Science has on business applications. The book will also include an overview of the different AI applications and their correlation between each other. The audience is graduate and postgraduate students, researchers, academicians, institutions, and professionals who are interested in exploring key technologies like Artificial Intelligence, Machine Learning, and Data Science.

State of the Art in Neural Networks and Their Applications

Author : Jasjit Suri
Publisher : Elsevier
ISBN 13 : 0128199121
Total Pages : 328 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis State of the Art in Neural Networks and Their Applications by : Jasjit Suri

Download or read book State of the Art in Neural Networks and Their Applications written by Jasjit Suri and published by Elsevier. This book was released on 2022-11-29 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: State of the Art in Neural Networks and Their Applications, Volume Two presents the latest advances in artificial neural networks and their applications across a wide range of clinical diagnoses. The book provides over views and case studies of advances in the role of machine learning, artificial intelligence, deep learning, cognitive image processing, and suitable data analytics useful for clinical diagnosis and research applications. The application of neural network, artificial intelligence and machine learning methods in biomedical image analysis have resulted in the development of computer-aided diagnostic (CAD) systems that aim towards the automatic early detection of several severe diseases. State of the Art in Neural Networks and Their Applications is presented in two volumes. Volume One: Neural Networks in Oncology Imaging covers lung cancer, prostate cancer, and bladder cancer. Volume Two: Neural Networks in Brain Disorders and Other Diseases covers autism spectrum disorder, Alzheimer’s disease, attention deficit hyperactivity disorder, hypertension, and other diseases. Written by experienced engineers in the field, these two volumes will help engineers, computer scientists, researchers, and clinicians understand the technology and applications of artificial neural networks. Includes applications of neural networks, AI, machine learning, and deep learning techniques to a variety of oncology imaging technologies Provides in-depth technical coverage of computer-aided diagnosis (CAD), including coverage of computer-aided classification, unified deep learning frameworks, 3D MRI, PET/CT, and more Covers deep learning cancer identification from histopathological images, medical image analysis, detection, segmentation and classification via AI

Notes on Medical Image Processing with Deep Learning

Author : Taposh Dutta Roy
Publisher :
ISBN 13 :
Total Pages : 62 pages
Book Rating : 4.5/5 (57 download)

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Book Synopsis Notes on Medical Image Processing with Deep Learning by : Taposh Dutta Roy

Download or read book Notes on Medical Image Processing with Deep Learning written by Taposh Dutta Roy and published by . This book was released on 2020-11-11 with total page 62 pages. Available in PDF, EPUB and Kindle. Book excerpt: Healthcare is a domain which deals variety of data - structured, semi-structured and un-structured data such as raw-text, images, sound, and sensory. A lot of research work has been focused on analyzing structured data from text sources. However, with the advent of better transducers and data processing capabilities we can connect these different types of data. This opens up a new paradigm to engage un-structured data with structured data. One such semi-structured data is Medical Image data. A lot of medical images are saved in various formats such as DICOM, NIFTI, JPEG and others. This document provides basic understanding in this area.How to use this book?This book covers the basics to do medical image processing and deep-learning. It provides papers to read and understand, general questions about the topic to think through and ponder, and advanced programming questions. If you follow through all the content, by the time you finish reading this small book, you would have gained enough knowledge to become a proficient in this area. Further, this area is changing faster than ever, so I will try to keep updating the content every year if possible.Why did I write this book?As I was researching on some of these areas, I wrote blog posts. Readers have been asking me for variety of questions on these. With this book, I am collecting all this information into one source, and providing a overview and connection of building blocks for medical image processing.My blog-post and links are here:Basics of GPU Computing for Data Scientists:https://medium.com/@taposhdr/gpu-s-have-become-the-new-core-for-image-analytics-b8ba8bd8d8f3Medical Image Analysis with Deep Learning - I:https://medium.com/@taposhdr/medical-image-analysis-with-deep-learning-i-23d518abf531Medical Image Analysis with Deep Learning - II:https://medium.com/@taposhdr/medical-image-analysis-with-deep-learning-ii-166532e964e6Medical Image Analysis with Deep Learning - III:https://medium.com/@taposhdr/medical-image-analysis-with-deep-learning-iii-eb01cc219aa2Medical Image Analysis with Deep Learning - IV:https://medium.com/@taposhdr/medical-image-analysis-with-deep-learning-iv-479b5fa446e7

Handbook On Big Data And Machine Learning In The Physical Sciences (In 2 Volumes)

Author :
Publisher : World Scientific
ISBN 13 : 9811204586
Total Pages : 1001 pages
Book Rating : 4.8/5 (112 download)

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Book Synopsis Handbook On Big Data And Machine Learning In The Physical Sciences (In 2 Volumes) by :

Download or read book Handbook On Big Data And Machine Learning In The Physical Sciences (In 2 Volumes) written by and published by World Scientific. This book was released on 2020-03-10 with total page 1001 pages. Available in PDF, EPUB and Kindle. Book excerpt: This compendium provides a comprehensive collection of the emergent applications of big data, machine learning, and artificial intelligence technologies to present day physical sciences ranging from materials theory and imaging to predictive synthesis and automated research. This area of research is among the most rapidly developing in the last several years in areas spanning materials science, chemistry, and condensed matter physics.Written by world renowned researchers, the compilation of two authoritative volumes provides a distinct summary of the modern advances in instrument — driven data generation and analytics, establishing the links between the big data and predictive theories, and outlining the emerging field of data and physics-driven predictive and autonomous systems.

Handbook of Research on Pattern Engineering System Development for Big Data Analytics

Author : Tiwari, Vivek
Publisher : IGI Global
ISBN 13 : 1522538712
Total Pages : 396 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Handbook of Research on Pattern Engineering System Development for Big Data Analytics by : Tiwari, Vivek

Download or read book Handbook of Research on Pattern Engineering System Development for Big Data Analytics written by Tiwari, Vivek and published by IGI Global. This book was released on 2018-04-20 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the growing use of web applications and communication devices, the use of data has increased throughout various industries. It is necessary to develop new techniques for managing data in order to ensure adequate usage. The Handbook of Research on Pattern Engineering System Development for Big Data Analytics is a critical scholarly resource that examines the incorporation of pattern management in business technologies as well as decision making and prediction process through the use of data management and analysis. Featuring coverage on a broad range of topics such as business intelligence, feature extraction, and data collection, this publication is geared towards professionals, academicians, practitioners, and researchers seeking current research on the development of pattern management systems for business applications.

Handbook of Data Science Approaches for Biomedical Engineering

Author : Valentina Emilia Balas
Publisher : Academic Press
ISBN 13 : 0128183195
Total Pages : 320 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Handbook of Data Science Approaches for Biomedical Engineering by : Valentina Emilia Balas

Download or read book Handbook of Data Science Approaches for Biomedical Engineering written by Valentina Emilia Balas and published by Academic Press. This book was released on 2019-11-13 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Data Science Approaches for Biomedical Engineering covers the research issues and concepts of biomedical engineering progress and the ways they are aligning with the latest technologies in IoT and big data. In addition, the book includes various real-time/offline medical applications that directly or indirectly rely on medical and information technology. Case studies in the field of medical science, i.e., biomedical engineering, computer science, information security, and interdisciplinary tools, along with modern tools and the technologies used are also included to enhance understanding. Today, the role of Big Data and IoT proves that ninety percent of data currently available has been generated in the last couple of years, with rapid increases happening every day. The reason for this growth is increasing in communication through electronic devices, sensors, web logs, global positioning system (GPS) data, mobile data, IoT, etc. Provides in-depth information about Biomedical Engineering with Big Data and Internet of Things Includes technical approaches for solving real-time healthcare problems and practical solutions through case studies in Big Data and Internet of Things Discusses big data applications for healthcare management, such as predictive analytics and forecasting, big data integration for medical data, algorithms and techniques to speed up the analysis of big medical data, and more

Recent Trends in Data Science and Soft Computing

Author : Faisal Saeed
Publisher : Springer
ISBN 13 : 3319990071
Total Pages : 1126 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Recent Trends in Data Science and Soft Computing by : Faisal Saeed

Download or read book Recent Trends in Data Science and Soft Computing written by Faisal Saeed and published by Springer. This book was released on 2018-09-08 with total page 1126 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the proceedings of the 3rd International Conference of Reliable Information and Communication Technology 2018 (IRICT 2018), which was held in Kuala Lumpur, Malaysia, on July 23–24, 2018. The main theme of the conference was “Data Science, AI and IoT Trends for the Fourth Industrial Revolution.” A total of 158 papers were submitted to the conference, of which 103 were accepted and considered for publication in this book. Several hot research topics are covered, including Advances in Data Science and Big Data Analytics, Artificial Intelligence and Soft Computing, Business Intelligence, Internet of Things (IoT) Technologies and Applications, Intelligent Communication Systems, Advances in Computer Vision, Health Informatics, Reliable Cloud Computing Environments, Recent Trends in Knowledge Management, Security Issues in the Cyber World, and Advances in Information Systems Research, Theories and Methods.

Proceedings of International Conference on Computational Intelligence, Data Science and Cloud Computing

Author : Valentina Emilia Balas
Publisher : Springer Nature
ISBN 13 : 9813349689
Total Pages : 795 pages
Book Rating : 4.8/5 (133 download)

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Book Synopsis Proceedings of International Conference on Computational Intelligence, Data Science and Cloud Computing by : Valentina Emilia Balas

Download or read book Proceedings of International Conference on Computational Intelligence, Data Science and Cloud Computing written by Valentina Emilia Balas and published by Springer Nature. This book was released on 2021 with total page 795 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes selected papers presented at International Conference on Computational Intelligence, Data Science and Cloud Computing (IEM-ICDC) 2020, organized by the Department of Information Technology, Institute of Engineering & Management, Kolkata, India, during 25-27 September 2020. It presents substantial new research findings about AI and robotics, image processing and NLP, cloud computing and big data analytics as well as in cyber security, blockchain and IoT, and various allied fields. The book serves as a reference resource for researchers and practitioners in academia and industry.