Trends in Deep Learning Methodologies

Trends in Deep Learning Methodologies
Author: Vincenzo Piuri,Sandeep Raj,Angelo Genovese,Rajshree Srivastava
Publsiher: Academic Press
Total Pages: 306
Release: 2020-11-30
ISBN 10: 0128222263
ISBN 13: 9780128222263
Language: EN, FR, DE, ES & NL

Trends in Deep Learning Methodologies Book Review:

Trends in Deep Learning Methodologies: Algorithms, Applications, and Systems covers deep learning approaches such as neural networks, deep belief networks, recurrent neural networks, convolutional neural networks, deep auto-encoder, and deep generative networks, which have emerged as powerful computational models. Chapters elaborate on these models which have shown significant success in dealing with massive data for a large number of applications, given their capacity to extract complex hidden features and learn efficient representation in unsupervised settings. Chapters investigate deep learning-based algorithms in a variety of application, including biomedical and health informatics, computer vision, image processing, and more. In recent years, many powerful algorithms have been developed for matching patterns in data and making predictions about future events. The major advantage of deep learning is to process big data analytics for better analysis and self-adaptive algorithms to handle more data. Deep learning methods can deal with multiple levels of representation in which the system learns to abstract higher level representations of raw data. Earlier, it was a common requirement to have a domain expert to develop a specific model for each specific application, however, recent advancements in representation learning algorithms allow researchers across various subject domains to automatically learn the patterns and representation of the given data for the development of specific models. Provides insights into the theory, algorithms, implementation and the application of deep learning techniques Covers a wide range of applications of deep learning across smart healthcare and smart engineering Investigates the development of new models and how they can be exploited to find appropriate solutions

Artificial Intelligence Trends for Data Analytics Using Machine Learning and Deep Learning Approaches

Artificial Intelligence Trends for Data Analytics Using Machine Learning and Deep Learning Approaches
Author: K. Gayathri Devi,Mamata Rath,Nguyen Thi Dieu Linh
Publsiher: CRC Press
Total Pages: 250
Release: 2020-10-07
ISBN 10: 1000179516
ISBN 13: 9781000179514
Language: EN, FR, DE, ES & NL

Artificial Intelligence Trends for Data Analytics Using Machine Learning and Deep Learning Approaches Book Review:

Artificial Intelligence (AI), when incorporated with machine learning and deep learning algorithms, has a wide variety of applications today. This book focuses on the implementation of various elementary and advanced approaches in AI that can be used in various domains to solve real-time decision-making problems. The book focuses on concepts and techniques used to run tasks in an automated manner. It discusses computational intelligence in the detection and diagnosis of clinical and biomedical images, covers the automation of a system through machine learning and deep learning approaches, presents data analytics and mining for decision-support applications, and includes case-based reasoning, natural language processing, computer vision, and AI approaches in real-time applications. Academic scientists, researchers, and students in the various domains of computer science engineering, electronics and communication engineering, and information technology, as well as industrial engineers, biomedical engineers, and management, will find this book useful. By the end of this book, you will understand the fundamentals of AI. Various case studies will develop your adaptive thinking to solve real-time AI problems. Features Includes AI-based decision-making approaches Discusses computational intelligence in the detection and diagnosis of clinical and biomedical images Covers automation of systems through machine learning and deep learning approaches and its implications to the real world Presents data analytics and mining for decision-support applications Offers case-based reasoning

Trends in Deep Learning Methodologies

Trends in Deep Learning Methodologies
Author: Vincenzo Piuri,Sandeep Raj,Angelo Genovese,Rajshree Srivastava
Publsiher: Academic Press
Total Pages: 306
Release: 2020-11-12
ISBN 10: 0128232684
ISBN 13: 9780128232682
Language: EN, FR, DE, ES & NL

Trends in Deep Learning Methodologies Book Review:

Trends in Deep Learning Methodologies: Algorithms, Applications, and Systems covers deep learning approaches such as neural networks, deep belief networks, recurrent neural networks, convolutional neural networks, deep auto-encoder, and deep generative networks, which have emerged as powerful computational models. Chapters elaborate on these models which have shown significant success in dealing with massive data for a large number of applications, given their capacity to extract complex hidden features and learn efficient representation in unsupervised settings. Chapters investigate deep learning-based algorithms in a variety of application, including biomedical and health informatics, computer vision, image processing, and more. In recent years, many powerful algorithms have been developed for matching patterns in data and making predictions about future events. The major advantage of deep learning is to process big data analytics for better analysis and self-adaptive algorithms to handle more data. Deep learning methods can deal with multiple levels of representation in which the system learns to abstract higher level representations of raw data. Earlier, it was a common requirement to have a domain expert to develop a specific model for each specific application, however, recent advancements in representation learning algorithms allow researchers across various subject domains to automatically learn the patterns and representation of the given data for the development of specific models. Provides insights into the theory, algorithms, implementation and the application of deep learning techniques Covers a wide range of applications of deep learning across smart healthcare and smart engineering Investigates the development of new models and how they can be exploited to find appropriate solutions

Deep Learning

Deep Learning
Author: Li Deng,Dong Yu
Publsiher: Unknown
Total Pages: 212
Release: 2014
ISBN 10: 9781601988140
ISBN 13: 1601988141
Language: EN, FR, DE, ES & NL

Deep Learning Book Review:

Provides an overview of general deep learning methodology and its applications to a variety of signal and information processing tasks

Handbook of Research on Emerging Trends and Applications of Machine Learning

Handbook of Research on Emerging Trends and Applications of Machine Learning
Author: Solanki, Arun,Kumar, Sandeep,Nayyar, Anand
Publsiher: IGI Global
Total Pages: 674
Release: 2019-12-13
ISBN 10: 1522596453
ISBN 13: 9781522596455
Language: EN, FR, DE, ES & NL

Handbook of Research on Emerging Trends and Applications of Machine Learning Book Review:

As today’s world continues to advance, Artificial Intelligence (AI) is a field that has become a staple of technological development and led to the advancement of numerous professional industries. An application within AI that has gained attention is machine learning. Machine learning uses statistical techniques and algorithms to give computer systems the ability to understand and its popularity has circulated through many trades. Understanding this technology and its countless implementations is pivotal for scientists and researchers across the world. The Handbook of Research on Emerging Trends and Applications of Machine Learning provides a high-level understanding of various machine learning algorithms along with modern tools and techniques using Artificial Intelligence. In addition, this book explores the critical role that machine learning plays in a variety of professional fields including healthcare, business, and computer science. While highlighting topics including image processing, predictive analytics, and smart grid management, this book is ideally designed for developers, data scientists, business analysts, information architects, finance agents, healthcare professionals, researchers, retail traders, professors, and graduate students seeking current research on the benefits, implementations, and trends of machine learning.

VLSI and Hardware Implementations using Modern Machine Learning Methods

VLSI and Hardware Implementations using Modern Machine Learning Methods
Author: Sandeep Saini,Kusum Lata,G.R. Sinha
Publsiher: CRC Press
Total Pages: 328
Release: 2021-12-31
ISBN 10: 1000523810
ISBN 13: 9781000523812
Language: EN, FR, DE, ES & NL

VLSI and Hardware Implementations using Modern Machine Learning Methods Book Review:

Machine learning is a potential solution to resolve bottleneck issues in VLSI via optimizing tasks in the design process. This book aims to provide the latest machine-learning–based methods, algorithms, architectures, and frameworks designed for VLSI design. The focus is on digital, analog, and mixed-signal design techniques, device modeling, physical design, hardware implementation, testability, reconfigurable design, synthesis and verification, and related areas. Chapters include case studies as well as novel research ideas in the given field. Overall, the book provides practical implementations of VLSI design, IC design, and hardware realization using machine learning techniques. Features: Provides the details of state-of-the-art machine learning methods used in VLSI design Discusses hardware implementation and device modeling pertaining to machine learning algorithms Explores machine learning for various VLSI architectures and reconfigurable computing Illustrates the latest techniques for device size and feature optimization Highlights the latest case studies and reviews of the methods used for hardware implementation This book is aimed at researchers, professionals, and graduate students in VLSI, machine learning, electrical and electronic engineering, computer engineering, and hardware systems.

Deep Learning Techniques and Optimization Strategies in Big Data Analytics

Deep Learning Techniques and Optimization Strategies in Big Data Analytics
Author: Thomas, J. Joshua,Karagoz, Pinar,Ahamed, B. Bazeer,Vasant, Pandian
Publsiher: IGI Global
Total Pages: 355
Release: 2019-11-29
ISBN 10: 1799811948
ISBN 13: 9781799811947
Language: EN, FR, DE, ES & NL

Deep Learning Techniques and Optimization Strategies in Big Data Analytics Book Review:

Many approaches have sprouted from artificial intelligence (AI) and produced major breakthroughs in the computer science and engineering industries. Deep learning is a method that is transforming the world of data and analytics. Optimization of this new approach is still unclear, however, and there’s a need for research on the various applications and techniques of deep learning in the field of computing. Deep Learning Techniques and Optimization Strategies in Big Data Analytics is a collection of innovative research on the methods and applications of deep learning strategies in the fields of computer science and information systems. While highlighting topics including data integration, computational modeling, and scheduling systems, this book is ideally designed for engineers, IT specialists, data analysts, data scientists, engineers, researchers, academicians, and students seeking current research on deep learning methods and its application in the digital industry.

Handbook of Research on Machine Learning Applications and Trends Algorithms Methods and Techniques

Handbook of Research on Machine Learning Applications and Trends  Algorithms  Methods  and Techniques
Author: Olivas, Emilio Soria,Guerrero, Jos‚ David Mart¡n,Martinez-Sober, Marcelino,Magdalena-Benedito, Jose Rafael,Serrano L¢pez, Antonio Jos‚
Publsiher: IGI Global
Total Pages: 852
Release: 2009-08-31
ISBN 10: 1605667676
ISBN 13: 9781605667676
Language: EN, FR, DE, ES & NL

Handbook of Research on Machine Learning Applications and Trends Algorithms Methods and Techniques Book Review:

"This book investiges machine learning (ML), one of the most fruitful fields of current research, both in the proposal of new techniques and theoretic algorithms and in their application to real-life problems"--Provided by publisher.

Proceedings of the 2nd International Conference on Recent Trends in Machine Learning IoT Smart Cities and Applications

Proceedings of the 2nd International Conference on Recent Trends in Machine Learning  IoT  Smart Cities and Applications
Author: Vinit Kumar Gunjan,Jacek M. Zurada
Publsiher: Springer Nature
Total Pages: 827
Release: 2022-01-10
ISBN 10: 9811664072
ISBN 13: 9789811664076
Language: EN, FR, DE, ES & NL

Proceedings of the 2nd International Conference on Recent Trends in Machine Learning IoT Smart Cities and Applications Book Review:

This book contains original, peer-reviewed research articles from the Second International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications, held in March 28-29th 2021 at CMR Institute of Technology, Hyderabad, Telangana India. It covers the latest research trends and developments in areas of machine learning, artificial intelligence, neural networks, cyber-physical systems, cybernetics, with emphasis on applications in smart cities, Internet of Things, practical data science and cognition. The book focuses on the comprehensive tenets of artificial intelligence, machine learning and deep learning to emphasize its use in modelling, identification, optimization, prediction, forecasting and control of future intelligent systems. Submissions were solicited of unpublished material, and present in-depth fundamental research contributions from a methodological/application perspective in understanding artificial intelligence and machine learning approaches and their capabilities in solving a diverse range of problems in industries and its real-world applications.

Machine Learning Concepts Methodologies Tools and Applications

Machine Learning  Concepts  Methodologies  Tools and Applications
Author: Management Association, Information Resources
Publsiher: IGI Global
Total Pages: 2124
Release: 2011-07-31
ISBN 10: 1609608194
ISBN 13: 9781609608194
Language: EN, FR, DE, ES & NL

Machine Learning Concepts Methodologies Tools and Applications Book Review:

"This reference offers a wide-ranging selection of key research in a complex field of study,discussing topics ranging from using machine learning to improve the effectiveness of agents and multi-agent systems to developing machine learning software for high frequency trading in financial markets"--Provided by publishe

Machine Learning Applications

Machine Learning Applications
Author: Rik Das,Siddhartha Bhattacharyya,Sudarshan Nandy
Publsiher: Walter de Gruyter GmbH & Co KG
Total Pages: 153
Release: 2020-04-20
ISBN 10: 3110608669
ISBN 13: 9783110608663
Language: EN, FR, DE, ES & NL

Machine Learning Applications Book Review:

The publication is attempted to address emerging trends in machine learning applications. Recent trends in information identification have identified huge scope in applying machine learning techniques for gaining meaningful insights. Random growth of unstructured data poses new research challenges to handle this huge source of information. Efficient designing of machine learning techniques is the need of the hour. Recent literature in machine learning has emphasized on single technique of information identification. Huge scope exists in developing hybrid machine learning models with reduced computational complexity for enhanced accuracy of information identification. This book will focus on techniques to reduce feature dimension for designing light weight techniques for real time identification and decision fusion. Key Findings of the book will be the use of machine learning in daily lives and the applications of it to improve livelihood. However, it will not be able to cover the entire domain in machine learning in its limited scope. This book is going to benefit the research scholars, entrepreneurs and interdisciplinary approaches to find new ways of applications in machine learning and thus will have novel research contributions. The lightweight techniques can be well used in real time which will add value to practice.

New Trends in the Use of Artificial Intelligence for the Industry 4 0

New Trends in the Use of Artificial Intelligence for the Industry 4 0
Author: Luis Romeral Martinez,Roque A. Osornio-Rios,Miguel Delgado Prieto
Publsiher: BoD – Books on Demand
Total Pages: 212
Release: 2020-03-25
ISBN 10: 1838801413
ISBN 13: 9781838801410
Language: EN, FR, DE, ES & NL

New Trends in the Use of Artificial Intelligence for the Industry 4 0 Book Review:

Industry 4.0 is based on the cyber-physical transformation of processes, systems and methods applied in the manufacturing sector, and on its autonomous and decentralized operation. Industry 4.0 reflects that the industrial world is at the beginning of the so-called Fourth Industrial Revolution, characterized by a massive interconnection of assets and the integration of human operators with the manufacturing environment. In this regard, data analytics and, specifically, the artificial intelligence is the vehicular technology towards the next generation of smart factories.Chapters in this book cover a diversity of current and new developments in the use of artificial intelligence on the industrial sector seen from the fourth industrial revolution point of view, namely, cyber-physical applications, artificial intelligence technologies and tools, Industrial Internet of Things and data analytics. This book contains high-quality chapters containing original research results and literature review of exceptional merit. Thus, it is in the aim of the book to contribute to the literature of the topic in this regard and let the readers know current and new trends in the use of artificial intelligence for the Industry 4.0.

Handbook of Research on Applications and Implementations of Machine Learning Techniques

Handbook of Research on Applications and Implementations of Machine Learning Techniques
Author: Sathiyamoorthi Velayutham
Publsiher: IGI Gloval, Engineering Science Reference
Total Pages: 461
Release: 2019-07
ISBN 10: 9781522599029
ISBN 13: 1522599029
Language: EN, FR, DE, ES & NL

Handbook of Research on Applications and Implementations of Machine Learning Techniques Book Review:

"This book examines the practical applications and implementation of various machine learning techniques in various fields such as agriculture, medical, image processing, and networking"--

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

Proceedings of International Conference on Recent Trends in Machine Learning  IoT  Smart Cities and Applications
Author: Vinit Kumar Gunjan,Jacek M. Zurada
Publsiher: Springer Nature
Total Pages: 998
Release: 2020-10-17
ISBN 10: 9811572348
ISBN 13: 9789811572340
Language: EN, FR, DE, ES & NL

Proceedings of International Conference on Recent Trends in Machine Learning IoT Smart Cities and Applications Book Review:

This book gathers selected research papers presented at the International Conference on Recent Trends in Machine Learning, IOT, Smart Cities & Applications (ICMISC 2020), held on 29–30 March 2020 at CMR Institute of Technology, Hyderabad, Telangana, India. Discussing current trends in machine learning, Internet of things, and smart cities applications, with a focus on multi-disciplinary research in the area of artificial intelligence and cyber-physical systems, this book is a valuable resource for scientists, research scholars and PG students wanting formulate their research ideas and find the future directions in these areas. Further, it serves as a reference work anyone wishing to understand the latest technologies used by practicing engineers around the globe.

Deep Learning for Personalized Healthcare Services

Deep Learning for Personalized Healthcare Services
Author: Vishal Jain,Jyotir Moy Chatterjee,Hadi Hedayati,Salahddine Krit,Omer Deperlioglu
Publsiher: Walter de Gruyter GmbH & Co KG
Total Pages: 268
Release: 2021-10-25
ISBN 10: 3110708175
ISBN 13: 9783110708172
Language: EN, FR, DE, ES & NL

Deep Learning for Personalized Healthcare Services Book Review:

This book uncovers the stakes and possibilities involved in realising personalised healthcare services through efficient and effective deep learning algorithms, enabling the healthcare industry to develop meaningful and cost-effective services. This requires effective understanding, application and amalgamation of deep learning with several other computing technologies, such as machine learning, data mining, and natural language processing.

AI and Deep Learning in Biometric Security

AI and Deep Learning in Biometric Security
Author: Gaurav Jaswal,Vivek Kanhangad,Raghavendra Ramachandra
Publsiher: CRC Press
Total Pages: 378
Release: 2021-03-22
ISBN 10: 1000291669
ISBN 13: 9781000291667
Language: EN, FR, DE, ES & NL

AI and Deep Learning in Biometric Security Book Review:

This book provides an in-depth overview of artificial intelligence and deep learning approaches with case studies to solve problems associated with biometric security such as authentication, indexing, template protection, spoofing attack detection, ROI detection, gender classification etc. This text highlights a showcase of cutting-edge research on the use of convolution neural networks, autoencoders, recurrent convolutional neural networks in face, hand, iris, gait, fingerprint, vein, and medical biometric traits. It also provides a step-by-step guide to understanding deep learning concepts for biometrics authentication approaches and presents an analysis of biometric images under various environmental conditions. This book is sure to catch the attention of scholars, researchers, practitioners, and technology aspirants who are willing to research in the field of AI and biometric security.

Machine Learning and Deep Learning Techniques in Wireless and Mobile Networking Systems

Machine Learning and Deep Learning Techniques in Wireless and Mobile Networking Systems
Author: K. Suganthi,R. Karthik,G. Rajesh,Peter Ho Chiung Ching
Publsiher: CRC Press
Total Pages: 296
Release: 2021-09-14
ISBN 10: 1000441814
ISBN 13: 9781000441819
Language: EN, FR, DE, ES & NL

Machine Learning and Deep Learning Techniques in Wireless and Mobile Networking Systems Book Review:

This book offers the latest advances and results in the fields of Machine Learning and Deep Learning for Wireless Communication and provides positive and critical discussions on the challenges and prospects. It provides a broad spectrum in understanding the improvements in Machine Learning and Deep Learning that are motivating by the specific constraints posed by wireless networking systems. The book offers an extensive overview on intelligent Wireless Communication systems and its underlying technologies, research challenges, solutions, and case studies. It provides information on intelligent wireless communication systems and its models, algorithms and applications. The book is written as a reference that offers the latest technologies and research results to various industry problems.

Deep Learning Approaches to Cloud Security

Deep Learning Approaches to Cloud Security
Author: Pramod Singh Rathore,Vishal Dutt,Rashmi Agrawal,Satya Murthy Sasubilli,Srinivasa Rao Swarna
Publsiher: John Wiley & Sons
Total Pages: 294
Release: 2022-02-08
ISBN 10: 1119760526
ISBN 13: 9781119760528
Language: EN, FR, DE, ES & NL

Deep Learning Approaches to Cloud Security Book Review:

DEEP LEARNING APPROACHES TO CLOUD SECURITY Covering one of the most important subjects to our society today, cloud security, this editorial team delves into solutions taken from evolving deep learning approaches, solutions allowing computers to learn from experience and understand the world in terms of a hierarchy of concepts, with each concept defined through its relation to simpler concepts. Deep learning is the fastest growing field in computer science. Deep learning algorithms and techniques are found to be useful in different areas like automatic machine translation, automatic handwriting generation, visual recognition, fraud detection, and detecting developmental delay in children. However, applying deep learning techniques or algorithms successfully in these areas needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to visualization. This book provides state of the art approaches of deep learning in these areas, including areas of detection and prediction, as well as future framework development, building service systems and analytical aspects. In all these topics, deep learning approaches, such as artificial neural networks, fuzzy logic, genetic algorithms, and hybrid mechanisms are used. This book is intended for dealing with modeling and performance prediction of the efficient cloud security systems, thereby bringing a newer dimension to this rapidly evolving field. This groundbreaking new volume presents these topics and trends of deep learning, bridging the research gap, and presenting solutions to the challenges facing the engineer or scientist every day in this area. Whether for the veteran engineer or the student, this is a must-have for any library. Deep Learning Approaches to Cloud Security: Is the first volume of its kind to go in-depth on the newest trends and innovations in cloud security through the use of deep learning approaches Covers these important new innovations, such as AI, data mining, and other evolving computing technologies in relation to cloud security Is a useful reference for the veteran computer scientist or engineer working in this area or an engineer new to the area, or a student in this area Discusses not just the practical applications of these technologies, but also the broader concepts and theory behind how these deep learning tools are vital not just to cloud security, but society as a whole Audience: Computer scientists, scientists and engineers working with information technology, design, network security, and manufacturing, researchers in computers, electronics, and electrical and network security, integrated domain, and data analytics, and students in these areas

Research Anthology on Machine Learning Techniques Methods and Applications

Research Anthology on Machine Learning Techniques  Methods  and Applications
Author: Management Association, Information Resources
Publsiher: IGI Global
Total Pages: 1516
Release: 2022-05-13
ISBN 10: 1668462923
ISBN 13: 9781668462928
Language: EN, FR, DE, ES & NL

Research Anthology on Machine Learning Techniques Methods and Applications Book Review:

Machine learning continues to have myriad applications across industries and fields. To ensure this technology is utilized appropriately and to its full potential, organizations must better understand exactly how and where it can be adapted. Further study on the applications of machine learning is required to discover its best practices, challenges, and strategies. The Research Anthology on Machine Learning Techniques, Methods, and Applications provides a thorough consideration of the innovative and emerging research within the area of machine learning. The book discusses how the technology has been used in the past as well as potential ways it can be used in the future to ensure industries continue to develop and grow. Covering a range of topics such as artificial intelligence, deep learning, cybersecurity, and robotics, this major reference work is ideal for computer scientists, managers, researchers, scholars, practitioners, academicians, instructors, and students.

Trends and Applications of Text Summarization Techniques

Trends and Applications of Text Summarization Techniques
Author: Fiori, Alessandro
Publsiher: IGI Global
Total Pages: 335
Release: 2019-08-30
ISBN 10: 1522593756
ISBN 13: 9781522593751
Language: EN, FR, DE, ES & NL

Trends and Applications of Text Summarization Techniques Book Review:

While the availability of electronic documents increases exponentially with advancing technology, the time spent to process this wealth of resourceful information decreases. Content analysis and information extraction must be aided by summarization methods to quickly parcel pieces of interest and allow for succinct user familiarization in a simple, efficient manner. Trends and Applications of Text Summarization Techniques is a pivotal reference source that explores the latest approaches of document summarization including update, multi-lingual, and domain-oriented summarization tasks and examines their current real-world applications in multiple fields. Featuring coverage on a wide range of topics such as parallel construction, social network integration, and evaluation metrics, this book is ideally designed for information technology practitioners, computer scientists, bioinformatics analysts, business managers, healthcare professionals, academicians, researchers, and students.