Trends in Deep Learning Methodologies Book

Trends in Deep Learning Methodologies


  • Author : Vincenzo Piuri
  • Publisher : Academic Press
  • Release Date : 2020-11-30
  • Genre: Computers
  • Pages : 306
  • ISBN 10 : 9780128222263

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Trends in Deep Learning Methodologies Excerpt :

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 Book

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


  • Author : K. Gayathri Devi
  • Publisher : CRC Press
  • Release Date : 2020-10-07
  • Genre: Computers
  • Pages : 250
  • ISBN 10 : 9781000179514

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

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

Deep Learning Book

Deep Learning


  • Author : Li Deng
  • Publisher : Unknown
  • Release Date : 2014
  • Genre: Machine learning
  • Pages : 212
  • ISBN 10 : 1601988141

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Deep Learning Excerpt :

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

Trends in Deep Learning Methodologies Book

Trends in Deep Learning Methodologies


  • Author : Vincenzo Piuri
  • Publisher : Academic Press
  • Release Date : 2020-11-12
  • Genre: Computers
  • Pages : 306
  • ISBN 10 : 9780128232682

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Trends in Deep Learning Methodologies Excerpt :

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

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

Handbook of Research on Emerging Trends and Applications of Machine Learning


  • Author : Solanki, Arun
  • Publisher : IGI Global
  • Release Date : 2019-12-13
  • Genre: Computers
  • Pages : 674
  • ISBN 10 : 9781522596455

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Handbook of Research on Emerging Trends and Applications of Machine Learning Excerpt :

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.

Machine Learning Applications Book

Machine Learning Applications


  • Author : Rik Das
  • Publisher : Walter de Gruyter GmbH & Co KG
  • Release Date : 2020-04-20
  • Genre: Computers
  • Pages : 153
  • ISBN 10 : 9783110608663

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Machine Learning Applications Excerpt :

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.

Deep Learning  Fundamentals  Theory and Applications Book

Deep Learning Fundamentals Theory and Applications


  • Author : Kaizhu Huang
  • Publisher : Springer
  • Release Date : 2019-02-15
  • Genre: Medical
  • Pages : 163
  • ISBN 10 : 9783030060732

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Deep Learning Fundamentals Theory and Applications Excerpt :

The purpose of this edited volume is to provide a comprehensive overview on the fundamentals of deep learning, introduce the widely-used learning architectures and algorithms, present its latest theoretical progress, discuss the most popular deep learning platforms and data sets, and describe how many deep learning methodologies have brought great breakthroughs in various applications of text, image, video, speech and audio processing. Deep learning (DL) has been widely considered as the next generation of machine learning methodology. DL attracts much attention and also achieves great success in pattern recognition, computer vision, data mining, and knowledge discovery due to its great capability in learning high-level abstract features from vast amount of data. This new book will not only attempt to provide a general roadmap or guidance to the current deep learning methodologies, but also present the challenges and envision new perspectives which may lead to further breakthroughs in this field. This book will serve as a useful reference for senior (undergraduate or graduate) students in computer science, statistics, electrical engineering, as well as others interested in studying or exploring the potential of exploiting deep learning algorithms. It will also be of special interest to researchers in the area of AI, pattern recognition, machine learning and related areas, alongside engineers interested in applying deep learning models in existing or new practical applications.

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

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


  • Author : Olivas, Emilio Soria
  • Publisher : IGI Global
  • Release Date : 2009-08-31
  • Genre: Computers
  • Pages : 852
  • ISBN 10 : 9781605667676

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

"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.

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

Handbook of Research on Applications and Implementations of Machine Learning Techniques


  • Author : Sathiyamoorthi Velayutham
  • Publisher : IGI Gloval, Engineering Science Reference
  • Release Date : 2019-07
  • Genre: Machine learning
  • Pages : 461
  • ISBN 10 : 1522599029

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Handbook of Research on Applications and Implementations of Machine Learning Techniques Excerpt :

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

AI and Deep Learning in Biometric Security Book

AI and Deep Learning in Biometric Security


  • Author : Gaurav Jaswal
  • Publisher : CRC Press
  • Release Date : 2021-03-22
  • Genre: Technology & Engineering
  • Pages : 378
  • ISBN 10 : 9781000291667

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AI and Deep Learning in Biometric Security Excerpt :

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.

VLSI and Hardware Implementations using Modern Machine Learning Methods Book

VLSI and Hardware Implementations using Modern Machine Learning Methods


  • Author : Sandeep Saini
  • Publisher : CRC Press
  • Release Date : 2021-12-31
  • Genre: Technology & Engineering
  • Pages : 328
  • ISBN 10 : 9781000523812

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VLSI and Hardware Implementations using Modern Machine Learning Methods Excerpt :

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.

Recent Trends in Computational Intelligence Enabled Research Book

Recent Trends in Computational Intelligence Enabled Research


  • Author : Siddhartha Bhattacharyya
  • Publisher : Academic Press
  • Release Date : 2021-07-31
  • Genre: Computers
  • Pages : 418
  • ISBN 10 : 9780323851794

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Recent Trends in Computational Intelligence Enabled Research Excerpt :

The field of computational intelligence has grown tremendously over that past five years, thanks to evolving soft computing and artificial intelligent methodologies, tools and techniques for envisaging the essence of intelligence embedded in real life observations. Consequently, scientists have been able to explain and understand real life processes and practices which previously often remain unexplored by virtue of their underlying imprecision, uncertainties and redundancies, and the unavailability of appropriate methods for describing the incompleteness and vagueness of information represented. With the advent of the field of computational intelligence, researchers are now able to explore and unearth the intelligence, otherwise insurmountable, embedded in the systems under consideration. Computational Intelligence is now not limited to only specific computational fields, it has made inroads in signal processing, smart manufacturing, predictive control, robot navigation, smart cities, and sensor design to name a few. Recent Trends in Computational Intelligence Enabled Research: Theoretical Foundations and Applications explores the use of this computational paradigm across a wide range of applied domains which handle meaningful information. Chapters investigate a broad spectrum of the applications of computational intelligence across different platforms and disciplines, expanding our knowledge base of various research initiatives in this direction. This volume aims to bring together researchers, engineers, developers and practitioners from academia and industry working in all major areas and interdisciplinary areas of computational intelligence, communication systems, computer networks, and soft computing. Provides insights into the theory, algorithms, implementation, and application of computational intelligence techniques Covers a wide range of applications of deep learning across various domains which are researching the applications of computational intelligence

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

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


  • Author : Vinit Kumar Gunjan
  • Publisher : Springer Nature
  • Release Date : 2022-01-10
  • Genre: Technology & Engineering
  • Pages : 827
  • ISBN 10 : 9789811664076

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

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.

Deep Learning and Neural Networks Book

Deep Learning and Neural Networks


  • Author : Information Resources Management Association
  • Publisher : Engineering Science Reference
  • Release Date : 2019
  • Genre: Big data
  • Pages : 2250
  • ISBN 10 : 1799804143

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Deep Learning and Neural Networks Excerpt :

"This book is a vital reference source that trends in data analytics and potential technologies that will facilitate insight in various domains of science, industry, business, and consumer applications. It also explores the latest concepts, algorithms, and techniques of deep learning and data mining and analysis"--

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

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


  • Author : Vinit Kumar Gunjan
  • Publisher : Springer Nature
  • Release Date : 2020-10-17
  • Genre: Technology & Engineering
  • Pages : 998
  • ISBN 10 : 9789811572340

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

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.