Automatic Channel Detection Using Deep Learning

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Automatic Channel Detection Using Deep Learning

Author : Nam Phuong Pham
Publisher :
ISBN 13 :
Total Pages : 192 pages
Book Rating : 4.:/5 (11 download)

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Book Synopsis Automatic Channel Detection Using Deep Learning by : Nam Phuong Pham

Download or read book Automatic Channel Detection Using Deep Learning written by Nam Phuong Pham and published by . This book was released on 2019 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: Picking 3D channel geobodies in seismic volumes is an important objective in seismic interpretation for hydrocarbon exploration. Manual detection of channel geobodies is a time-consuming and subjective process. The interpreter can calculate different seismic attributes such as coherence to aid for manual detection of channel geobodies in seismic volumes. However, these attributes still do not directly identify 3D channel geobodies. Machine learning and deep learning are data-driven techniques that have been getting more attention recently in different fields, such as medical imaging and computer vision. With large volumes of available data in different types and a development of powerful computational resources, geophysics is a promising field for applying machine learning and deep learning. Many seismic interpretation steps are analogous to different problems in computer vision that have been solved successfully using deep learning. Channel detection in seismic volumes is analogous to segmentation problems for images. Applying deep learning to seismic interpretations, specifically to automatic channel detection in 3D seismic volumes, can make the process faster and the workflow less subjective. Decision-making based on interpretations is uncertain; so uncertainties in interpretation results are very important. Deep learning with different algorithms can also help interpreters quantify this uncertainty.

The TensorFlow Workshop

Author : Matthew Moocarme
Publisher : Packt Publishing Ltd
ISBN 13 : 1800200226
Total Pages : 601 pages
Book Rating : 4.8/5 (2 download)

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Book Synopsis The TensorFlow Workshop by : Matthew Moocarme

Download or read book The TensorFlow Workshop written by Matthew Moocarme and published by Packt Publishing Ltd. This book was released on 2021-12-15 with total page 601 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get started with TensorFlow fundamentals to build and train deep learning models with real-world data, practical exercises, and challenging activities Key FeaturesUnderstand the fundamentals of tensors, neural networks, and deep learningDiscover how to implement and fine-tune deep learning models for real-world datasetsBuild your experience and confidence with hands-on exercises and activitiesBook Description Getting to grips with tensors, deep learning, and neural networks can be intimidating and confusing for anyone, no matter their experience level. The breadth of information out there, often written at a very high level and aimed at advanced practitioners, can make getting started even more challenging. If this sounds familiar to you, The TensorFlow Workshop is here to help. Combining clear explanations, realistic examples, and plenty of hands-on practice, it'll quickly get you up and running. You'll start off with the basics – learning how to load data into TensorFlow, perform tensor operations, and utilize common optimizers and activation functions. As you progress, you'll experiment with different TensorFlow development tools, including TensorBoard, TensorFlow Hub, and Google Colab, before moving on to solve regression and classification problems with sequential models. Building on this solid foundation, you'll learn how to tune models and work with different types of neural network, getting hands-on with real-world deep learning applications such as text encoding, temperature forecasting, image augmentation, and audio processing. By the end of this deep learning book, you'll have the skills, knowledge, and confidence to tackle your own ambitious deep learning projects with TensorFlow. What you will learnGet to grips with TensorFlow's mathematical operationsPre-process a wide variety of tabular, sequential, and image dataUnderstand the purpose and usage of different deep learning layersPerform hyperparameter-tuning to prevent overfitting of training dataUse pre-trained models to speed up the development of learning modelsGenerate new data based on existing patterns using generative modelsWho this book is for This TensorFlow book is for anyone who wants to develop their understanding of deep learning and get started building neural networks with TensorFlow. Basic knowledge of Python programming and its libraries, as well as a general understanding of the fundamentals of data science and machine learning, will help you grasp the topics covered in this book more easily.

Deep Learning Techniques for Automation and Industrial Applications

Author : Pramod Singh Rathore
Publisher : John Wiley & Sons
ISBN 13 : 1394234252
Total Pages : 237 pages
Book Rating : 4.3/5 (942 download)

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Book Synopsis Deep Learning Techniques for Automation and Industrial Applications by : Pramod Singh Rathore

Download or read book Deep Learning Techniques for Automation and Industrial Applications written by Pramod Singh Rathore and published by John Wiley & Sons. This book was released on 2024-06-24 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides state-of-the-art approaches to deep learning in areas of detection and prediction, as well as future framework development, building service systems and analytical aspects in which artificial neural networks, fuzzy logic, genetic algorithms, and hybrid mechanisms are used. Deep learning algorithms and techniques are found to be useful in various areas, such as automatic machine translation, automatic handwriting generation, visual recognition, fraud detection, and detecting developmental delays in children. “Deep Learning Techniques for Automation and Industrial Applications” presents a concise introduction to the recent advances in this field of artificial intelligence (AI). The broad-ranging discussion covers the algorithms and applications in AI, reasoning, machine learning, neural networks, reinforcement learning, and their applications in various domains like agriculture, manufacturing, and healthcare. Applying deep learning techniques or algorithms successfully in these areas requires a concerted effort, fostering integrative research between experts from diverse disciplines from data science to visualization. This book provides state-of-the-art approaches to deep learning covering detection and prediction, as well as future framework development, building service systems, and analytical aspects. For all these topics, various approaches to deep learning, such as artificial neural networks, fuzzy logic, genetic algorithms, and hybrid mechanisms, are explained. Audience The book will be useful to researchers and industry engineers working in information technology, data analytics network security, and manufacturing. Graduate and upper-level undergraduate students in advanced modeling and simulation courses will find this book very useful.

Deep Learning and Its Applications for Vehicle Networks

Author : Fei Hu
Publisher : CRC Press
ISBN 13 : 100087723X
Total Pages : 357 pages
Book Rating : 4.0/5 (8 download)

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Book Synopsis Deep Learning and Its Applications for Vehicle Networks by : Fei Hu

Download or read book Deep Learning and Its Applications for Vehicle Networks written by Fei Hu and published by CRC Press. This book was released on 2023-05-12 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning (DL) is an effective approach for AI-based vehicular networks and can deliver a powerful set of tools for such vehicular network dynamics. In various domains of vehicular networks, DL can be used for learning-based channel estimation, traffic flow prediction, vehicle trajectory prediction, location-prediction-based scheduling and routing, intelligent network congestion control mechanism, smart load balancing and vertical handoff control, intelligent network security strategies, virtual smart and efficient resource allocation and intelligent distributed resource allocation methods. This book is based on the work from world-famous experts on the application of DL for vehicle networks. It consists of the following five parts: (I) DL for vehicle safety and security: This part covers the use of DL algorithms for vehicle safety or security. (II) DL for effective vehicle communications: Vehicle networks consist of vehicle-to-vehicle and vehicle-to-roadside communications. This part covers how Intelligent vehicle networks require a flexible selection of the best path across all vehicles, adaptive sending rate control based on bandwidth availability and timely data downloads from a roadside base-station. (III) DL for vehicle control: The myriad operations that require intelligent control for each individual vehicle are discussed in this part. This also includes emission control, which is based on the road traffic situation, the charging pile load is predicted through DL andvehicle speed adjustments based on the camera-captured image analysis. (IV) DL for information management: This part covers some intelligent information collection and understanding. We can use DL for energy-saving vehicle trajectory control based on the road traffic situation and given destination information; we can also natural language processing based on DL algorithm for automatic internet of things (IoT) search during driving. (V) Other applications. This part introduces the use of DL models for other vehicle controls. Autonomous vehicles are becoming more and more popular in society. The DL and its variants will play greater roles in cognitive vehicle communications and control. Other machine learning models such as deep reinforcement learning will also facilitate intelligent vehicle behavior understanding and adjustment. This book will become a valuable reference to your understanding of this critical field.

A Primer on Machine Learning in Subsurface Geosciences

Author : Shuvajit Bhattacharya
Publisher : Springer Nature
ISBN 13 : 3030717682
Total Pages : 172 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis A Primer on Machine Learning in Subsurface Geosciences by : Shuvajit Bhattacharya

Download or read book A Primer on Machine Learning in Subsurface Geosciences written by Shuvajit Bhattacharya and published by Springer Nature. This book was released on 2021-05-03 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides readers with a timely review and discussion of the success, promise, and perils of machine learning in geosciences. It explores the fundamentals of data science and machine learning, and how their advances have disrupted the traditional workflows used in the industry and academia, including geology, geophysics, petrophysics, geomechanics, and geochemistry. It then presents the real-world applications and explains that, while this disruption has affected the top-level executives, geoscientists as well as field operators in the industry and academia, machine learning will ultimately benefit these users. The book is written by a practitioner of machine learning and statistics, keeping geoscientists in mind. It highlights the need to go beyond concepts covered in STAT 101 courses and embrace new computational tools to solve complex problems in geosciences. It also offers practitioners, researchers, and academics insights into how to identify, develop, deploy, and recommend fit-for-purpose machine learning models to solve real-world problems in subsurface geosciences.

Real-Time Applications of Machine Learning in Cyber-Physical Systems

Author : Easwaran, Balamurugan
Publisher : IGI Global
ISBN 13 : 1799893103
Total Pages : 307 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Real-Time Applications of Machine Learning in Cyber-Physical Systems by : Easwaran, Balamurugan

Download or read book Real-Time Applications of Machine Learning in Cyber-Physical Systems written by Easwaran, Balamurugan and published by IGI Global. This book was released on 2022-03-11 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: Technological advancements of recent decades have reshaped the way people socialize, work, learn, and ultimately live. The use of cyber-physical systems (CPS) specifically have helped people lead their lives with greater control and freedom. CPS domains have great societal significance, providing crucial assistance in industries ranging from security to healthcare. At the same time, machine learning (ML) algorithms are known for being substantially efficient, high performing, and have become a real standard due to greater accessibility, and now more than ever, multidisciplinary applications of ML for CPS have become a necessity to help uncover constructive solutions for real-world problems. Real-Time Applications of Machine Learning in Cyber-Physical Systems provides a relevant theoretical framework and the most recent empirical findings on various real-time applications of machine learning in cyber-physical systems. Covering topics like intrusion detection systems, predictive maintenance, and seizure prediction, this book is an essential resource for researchers, machine learning professionals, independent researchers, scholars, scientists, libraries, and academicians.

Machine Learning for Future Wireless Communications

Author : Fa-Long Luo
Publisher : John Wiley & Sons
ISBN 13 : 1119562252
Total Pages : 490 pages
Book Rating : 4.1/5 (195 download)

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Book Synopsis Machine Learning for Future Wireless Communications by : Fa-Long Luo

Download or read book Machine Learning for Future Wireless Communications written by Fa-Long Luo and published by John Wiley & Sons. This book was released on 2020-02-10 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive review to the theory, application and research of machine learning for future wireless communications In one single volume, Machine Learning for Future Wireless Communications provides a comprehensive and highly accessible treatment to the theory, applications and current research developments to the technology aspects related to machine learning for wireless communications and networks. The technology development of machine learning for wireless communications has grown explosively and is one of the biggest trends in related academic, research and industry communities. Deep neural networks-based machine learning technology is a promising tool to attack the big challenge in wireless communications and networks imposed by the increasing demands in terms of capacity, coverage, latency, efficiency flexibility, compatibility, quality of experience and silicon convergence. The author – a noted expert on the topic – covers a wide range of topics including system architecture and optimization, physical-layer and cross-layer processing, air interface and protocol design, beamforming and antenna configuration, network coding and slicing, cell acquisition and handover, scheduling and rate adaption, radio access control, smart proactive caching and adaptive resource allocations. Uniquely organized into three categories: Spectrum Intelligence, Transmission Intelligence and Network Intelligence, this important resource: Offers a comprehensive review of the theory, applications and current developments of machine learning for wireless communications and networks Covers a range of topics from architecture and optimization to adaptive resource allocations Reviews state-of-the-art machine learning based solutions for network coverage Includes an overview of the applications of machine learning algorithms in future wireless networks Explores flexible backhaul and front-haul, cross-layer optimization and coding, full-duplex radio, digital front-end (DFE) and radio-frequency (RF) processing Written for professional engineers, researchers, scientists, manufacturers, network operators, software developers and graduate students, Machine Learning for Future Wireless Communications presents in 21 chapters a comprehensive review of the topic authored by an expert in the field.

Digital Health Approach for Predictive, Preventive, Personalised and Participatory Medicine

Author : Lotfi Chaari
Publisher : Springer
ISBN 13 : 3030118002
Total Pages : 88 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Digital Health Approach for Predictive, Preventive, Personalised and Participatory Medicine by : Lotfi Chaari

Download or read book Digital Health Approach for Predictive, Preventive, Personalised and Participatory Medicine written by Lotfi Chaari and published by Springer. This book was released on 2019-07-10 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt: This collection, entitled Digital Health for Predictive, Preventive, Personalized and Participatory Medicine contains the proceedings of the first International conference on digital healthtechnologies (ICDHT 2018). Ten recent contributions in the fields of Artificial Intelligence (AI) and machine learning, Internet of Things (IoT) and data analysis, all applied to digital health. This collection enables researchers to learn about recent advances in the above mentioned fields. It brings a technological viewpoint of P4 medicine. Readers will discover how advanced Information Technology (IT) tools can be used for healthcare. For instance, the use of connected objects to monitor physiological parameters is discussed. Moreover, even if compressed sensing is nowadays a common acquisition technique, its use for IoT is presented in this collection through one of the pioneer works in the field. In addition, the use of AI for epileptic seizure detection is also discussed as being one of the major concerns of predictive medicine both in industrialized and low-income countries. This work is edited by Prof. Lotfi Chaari, professor at the University of Sfax, and previously at the University of Toulouse. This work comes after more than ten years of expertise in the biomedical signal and image processing field.

Automatic CNN Channel Selection and Effective Detection on Face and Rotated Aerial Objects

Author : Zhenyu Fang
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (12 download)

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Book Synopsis Automatic CNN Channel Selection and Effective Detection on Face and Rotated Aerial Objects by : Zhenyu Fang

Download or read book Automatic CNN Channel Selection and Effective Detection on Face and Rotated Aerial Objects written by Zhenyu Fang and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Pragmatic Machine Learning with Python

Author : Avishek Nag
Publisher : BPB Publications
ISBN 13 : 938984536X
Total Pages : 365 pages
Book Rating : 4.3/5 (898 download)

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Book Synopsis Pragmatic Machine Learning with Python by : Avishek Nag

Download or read book Pragmatic Machine Learning with Python written by Avishek Nag and published by BPB Publications. This book was released on 2020-04-30 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: An easy-to-understand guide to learn practical Machine Learning techniques with Mathematical foundations KEY FEATURESÊ - A balanced combination of underlying mathematical theories & practical examples with Python code - Coverage of latest topics like multi-label classification, Text Mining, Doc2Vec, Word2Vec, XMeans clustering, unsupervised outlier detection, techniques to deploy ML models in production-grade systemsÊ with PMML, etc - Coverage of sufficient & relevant visualization techniques specific to any topic DESCRIPTIONÊ This book will be ideal for working professionals who want to learn Machine Learning from scratch. The first chapter will be an introductory chapter to make readers comfortable with the idea of Machine Learning and the required mathematical theories. There will be a balanced combination of underlying mathematical theories corresponding to any Machine Learning topic and its implementation using Python. Most of the implementations will be based on Ôscikit-learn,Õ but other Python libraries like ÔGensimÕ or ÔPyTorchÕ will also be used for some topics like text analytics or deep learning. The book will be divided into chapters based on primary Machine Learning topics like Classification, Regression, Clustering, Deep Learning, Text Mining, etc. The book will also explain different techniques of putting Machine Learning models into production-grade systems using Big Data or Non-Big Data flavors and standards for exporting models.Ê WHAT WILL YOU LEARNÊ - Get familiar with practical concepts of Machine Learning from ground zero - Learn how to deploy Machine Learning models in production - Understand how to do ÒData Science StorytellingÓÊ - Explore the latest topics in the current industry about Machine Learning WHO THIS BOOK IS FORÊÊ This book would be ideal for experienced Software Professionals who are trying to get into the field of Machine Learning. Anyone who wishes to Learn Machine Learning concepts and models in the production lifecycle. TABLE OF CONTENTS 1. Introduction to Machine Learning & Mathematical preliminaries 2. Classification 3. Regression 4. Clustering 5. Deep Learning & Neural Networks 6. Miscellaneous Unsupervised Learning 7. Text Mining 8. Machine Learning models in production 9. Case Studies & Data Science Storytelling

Intelligent Computing & Optimization

Author : Pandian Vasant
Publisher : Springer Nature
ISBN 13 : 3031199588
Total Pages : 1215 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis Intelligent Computing & Optimization by : Pandian Vasant

Download or read book Intelligent Computing & Optimization written by Pandian Vasant and published by Springer Nature. This book was released on 2022-10-20 with total page 1215 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book of Springer Nature is another proof of Springer’s outstanding and greatness on the lively interface of Smart Computational Optimization, Green ICT, Smart Intelligence and Machine Learning! It is a Master Piece of what our community of academics and experts can provide when an Interconnected Approach of Joint, Mutual and Meta Learning is supported by Modern Operational Research and Experience of the World-Leader Springer Nature! The 5th edition of International Conference on Intelligent Computing and Optimization took place at October 27–28, 2022, via Zoom. Objective was to celebrate “Creativity with Compassion and Wisdom” with researchers, scholars, experts and investigators in Intelligent Computing and Optimization across the planet, to share knowledge, experience, innovation—a marvelous opportunity for discourse and mutuality by novel research, invention and creativity. This proceedings book of ICO’2022 is published by Springer Nature—Quality Label of wonderful.

Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery

Author : Quan Xie
Publisher : Springer Nature
ISBN 13 : 3030896986
Total Pages : 1454 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery by : Quan Xie

Download or read book Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery written by Quan Xie and published by Springer Nature. This book was released on 2022-01-04 with total page 1454 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book consists of papers on the recent progresses in the state of the art in natural computation, fuzzy systems and knowledge discovery. The book can be useful for researchers, including professors, graduate students, as well as R & D staff in the industry, with a general interest in natural computation, fuzzy systems and knowledge discovery. The work printed in this book was presented at the 2021 17th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD 2021, 24–26 July 2021, Guiyang, China). All papers were rigorously peer-reviewed by experts in the areas.

Biophysics and Nanotechnology of Ion Channels

Author : Mohammad Ashrafuzzaman
Publisher : CRC Press
ISBN 13 : 1000451593
Total Pages : 318 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Biophysics and Nanotechnology of Ion Channels by : Mohammad Ashrafuzzaman

Download or read book Biophysics and Nanotechnology of Ion Channels written by Mohammad Ashrafuzzaman and published by CRC Press. This book was released on 2021-09-20 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive review of the biophysics and nanotechnology of ion channels. It details the biological and physiological entities of ion channels in cells and addresses various physical perspectives of ion channel structures and functions. Naturally inbuilt and artificial applicable nanotechnologies of ion channels are modelled and explored. It discusses various methods that can be utilized toward understanding ion channel-based cellular diseases. Physical, biochemical, biomedical, and bioinformatics techniques are taken into consideration to enable the development of strategies to address therapeutic drug discovery and delivery. This book will be of interest to advanced undergraduate and graduate students in biophysics and related biomedical sciences in addition to researchers in the field and industry. Features: Provides a stimulating introduction to the structures and functions of ion channels of biological cell membranes and discusses the biophysics of ion channels in condensed matter state and physiological condition Addresses natural processes and nanotechnology opportunities for their purposeful manipulation Lays the groundwork for vitally important medical advances Mohammad Ashrafuzzaman, a biophysicist and condensed matter scientist, is passionate about investigating biological and biochemical processes utilizing the principles and techniques of physics. He is an associate professor at King Saud University’s Biochemistry Department of College of Science, Riyadh, Saudi Arabia, the co-founder of MDT Canada Inc., and the founder of Child Life Development Institute, Edmonton, Canada. He also authored Nanoscale Biophysics of the Cell and Membrane Biophysics.

A Resilient Cognitive Detection with Automated Channel Selection for Enhanced Channel Management in Wireless Local Area Network

Author : Mohammad Nayeem Morshed
Publisher :
ISBN 13 :
Total Pages : 138 pages
Book Rating : 4.:/5 (112 download)

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Book Synopsis A Resilient Cognitive Detection with Automated Channel Selection for Enhanced Channel Management in Wireless Local Area Network by : Mohammad Nayeem Morshed

Download or read book A Resilient Cognitive Detection with Automated Channel Selection for Enhanced Channel Management in Wireless Local Area Network written by Mohammad Nayeem Morshed and published by . This book was released on 2017 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this research is to propose a resilient cognitive radio detection scheme with an automated channel selection algorithm, which is able to change SUs channel according to the user demand in real-time. As both the licensed and unlicensed radio resources are very limited to user demand, the PU detection is most important objective of this system, otherwise serious interference may occur to PUs. To achieve this goal, a threshold determination technique also needed to choose carefully for declaring a channel as absent of PU. Apart from these, mobility is still an issue to for real-time CR detection and communication over SUs. Considering these issues,the objectives of this research are ; to develop a simplePU channel detection method for mobile smartphones, which is able to detect the available PU channels automatically for a specific location and time period ; to investigatea specific range of threshold for real-time distinguishing between presence and absence of PUs and verify writing a custom Android application software ; to enhance and implement an automatic channel selection (ACS) algorithm to select the best channel automatically based on PU channel availability for unique radio resource management.

ICT Analysis and Applications

Author : Simon Fong
Publisher : Springer Nature
ISBN 13 : 9819965683
Total Pages : 623 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis ICT Analysis and Applications by : Simon Fong

Download or read book ICT Analysis and Applications written by Simon Fong and published by Springer Nature. This book was released on 2024-01-22 with total page 623 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book proposes new technologies and discusses future solutions for ICT design infrastructures, as reflected in high-quality papers presented at the 8th International Conference on ICT for Sustainable Development (ICT4SD 2023), held in Goa, India, on August 3–4, 2023. The book covers the topics such as big data and data mining, data fusion, IoT programming toolkits and frameworks, green communication systems and network, use of ICT in smart cities, sensor networks and embedded system, network and information security, wireless and optical networks, security, trust, and privacy, routing and control protocols, cognitive radio and networks, and natural language processing. Bringing together experts from different countries, the book explores a range of central issues from an international perspective.

Proceedings of 3rd International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications

Author : Vinit Kumar Gunjan
Publisher : Springer Nature
ISBN 13 : 9811960887
Total Pages : 682 pages
Book Rating : 4.8/5 (119 download)

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Book Synopsis Proceedings of 3rd International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications by : Vinit Kumar Gunjan

Download or read book Proceedings of 3rd International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications written by Vinit Kumar Gunjan and published by Springer Nature. This book was released on 2023-02-23 with total page 682 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is a collection of best selected research papers presented at the International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications (ICMISC 2022) held during 28 – 29 March 2022 at CMR Institute of Technology, Hyderabad, Telangana, India. This book will contain the articles on current trends of machine learning, internet of things, and smart cities applications emphasizing on multi-disciplinary research in the area of artificial intelligence and cyber physical systems. The book is a great resource for scientists, research scholars and PG students to formulate their research ideas and find the future directions in these areas. Further, this book serves as a reference work to understand the latest technologies by practice engineers across the globe.

Advanced Wireless Communication and Sensor Networks

Author : Ashish Bagwari
Publisher : CRC Press
ISBN 13 : 1000880346
Total Pages : 398 pages
Book Rating : 4.0/5 (8 download)

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Book Synopsis Advanced Wireless Communication and Sensor Networks by : Ashish Bagwari

Download or read book Advanced Wireless Communication and Sensor Networks written by Ashish Bagwari and published by CRC Press. This book was released on 2023-07-12 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers wireless communication, security issues, advanced wireless sensor networks (WSNs), routing protocols of WSNs with cross-layer solutions, emerging trends in the advanced WSNs, power management, distributed sensing and data gathering techniques for WSNs, WSNs security, applications, research of advanced WSNs with simulation results, and simulation tools for WSNs. Features: Covers technologies supporting advanced wireless communication systems, sensor networks, and the conceptual development of the subject. Discusses advanced data gathering and sharing/ distributed sensing techniques with its business applicability. Includes numerous worked-out mathematical equations and formulas, as well as essential principles including figures, illustrations, algorithms, and flow charts. Provides pervasive background knowledge including both wireless communications and WSNs. Covers wireless networks as well as sensor network models in detail. This book is aimed at graduate students, researchers, and academics working in the field of computer science, wireless communication technology, and advanced WSNs.