Trends in Deep Learning Methodologies

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  • Author : Vincenzo Piuri
  • Publisher : Academic Press
  • Pages : 306 pages
  • ISBN : 0128232684
  • Rating : /5 from reviews
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Download or Read online Trends in Deep Learning Methodologies full in PDF, ePub and kindle. this book written by Vincenzo Piuri and published by Academic Press which was released on 12 November 2020 with total page 306 pages. We cannot guarantee that Trends in Deep Learning Methodologies book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. 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

Trends in Deep Learning Methodologies

Trends in Deep Learning Methodologies
  • Author : Vincenzo Piuri,Sandeep Raj,Angelo Genovese,Rajshree Srivastava
  • Publisher : Academic Press
  • Release : 12 November 2020
GET THIS BOOK Trends in Deep Learning Methodologies

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

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
  • Publisher : CRC Press
  • Release : 30 December 2021
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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

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‚
  • Publisher : IGI Global
  • Release : 31 August 2009
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"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 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
  • Publisher : Springer Nature
  • Release : 17 October 2020
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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

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
  • Publisher : CRC Press
  • Release : 14 September 2021
GET THIS BOOK Machine Learning and Deep Learning Techniques in Wireless and Mobile Networking Systems

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

Research Anthology on Machine Learning Techniques Methods and Applications

Research Anthology on Machine Learning Techniques  Methods  and Applications
  • Author : Management Association, Information Resources
  • Publisher : IGI Global
  • Release : 13 May 2022
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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

Machine Learning Techniques for Smart City Applications Trends and Solutions

Machine Learning Techniques for Smart City Applications  Trends and Solutions
  • Author : D. Jude Hemanth
  • Publisher : Springer Nature
  • Release : 19 September 2022
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This book discusses the application of different machine learning techniques to the sub-concepts of smart cities such as smart energy, transportation, waste management, health, infrastructure, etc. The focus of this book is to come up with innovative solutions in the above-mentioned issues with the purpose of alleviating the pressing needs of human society. This book includes content with practical examples which are easy to understand for readers. It also covers a multi-disciplinary field and, consequently, it benefits a wide readership

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
  • Publisher : CRC Press
  • Release : 08 October 2020
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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

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
  • Publisher : IGI Global
  • Release : 13 December 2019
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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.

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
  • Publisher : John Wiley & Sons
  • Release : 26 January 2022
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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

Machine Learning Methods for Engineering Application Development

Machine Learning Methods for Engineering Application Development
  • Author : Prasad Lokulwar,Basant Verma,N. Thillaiarasu
  • Publisher : Bentham Science Publishers
  • Release : 11 November 2022
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This book is a quick review of machine learning methods for engineeringapplications. It provides an introduction to the principles of machine learningand common algorithms in the first section. Proceeding chapters summarize andanalyze the existing scholarly work and discuss some general issues in this field.Next, it offers some guidelines on applying machine learning methods to softwareengineering tasks. Finally, it gives an outlook into some of the futuredevelopments and possibly new research areas of machine learning and artificialintelligence in general.Techniques

Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics

Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics
  • Author : R. Sujatha,S. L. Aarthy,R. Vettriselvan
  • Publisher : CRC Press
  • Release : 22 September 2021
GET THIS BOOK Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics

Data science revolves around two giants: Big Data analytics and Deep Learning. It is becoming challenging to handle and retrieve useful information due to how fast data is expanding. This book presents the technologies and tools to simplify and streamline the formation of Big Data as well as Deep Learning systems. This book discusses how Big Data and Deep Learning hold the potential to significantly increase data understanding and decision-making. It also covers numerous applications in healthcare, education, communication, media,

Explainable Artificial Intelligence for Smart Cities

Explainable Artificial Intelligence for Smart Cities
  • Author : Mohamed Lahby,Utku Kose,Akash Kumar Bhoi
  • Publisher : CRC Press
  • Release : 10 November 2021
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Thanks to rapid technological developments in terms of Computational Intelligence, smart tools have been playing active roles in daily life. It is clear that the 21st century has brought about many advantages in using high-level computation and communication solutions to deal with real-world problems; however, more technologies bring more changes to society. In this sense, the concept of smart cities has been a widely discussed topic in terms of society and Artificial Intelligence-oriented research efforts. The rise of smart cities

Machine Learning Applications

Machine Learning Applications
  • Author : Rik Das,Siddhartha Bhattacharyya,Sudarshan Nandy
  • Publisher : Walter de Gruyter GmbH & Co KG
  • Release : 20 April 2020
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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

Artificial Intelligence and Machine Learning Methods in COVID 19 and Related Health Diseases

Artificial Intelligence and Machine Learning Methods in COVID 19 and Related Health Diseases
  • Author : Victor Chang,Harleen Kaur,Simon James Fong
  • Publisher : Springer Nature
  • Release : 28 June 2022
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This Springer book provides a perfect platform to submit chapters that discuss the prospective developments and innovative ideas in artificial intelligence and machine learning techniques in the diagnosis of COVID-19. COVID-19 is a huge challenge to humanity and the medical sciences. So far as of today, we have been unable to find a medical solution (Vaccine). However, globally, we are still managing the use of technology for our work, communications, analytics, and predictions with the use of advancement in data