Trends in Deep Learning Methodologies

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  • Author : Vincenzo Piuri
  • Publisher : Academic Press
  • Pages : 306 pages
  • ISBN : 0128232684
  • Rating : /5 from reviews
CLICK HERE TO GET THIS BOOK >>>Trends in Deep Learning Methodologies

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 01 December 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 : 01 December 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

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

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

Machine Learning Applications

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

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

Adversary Aware Learning Techniques and Trends in Cybersecurity

Adversary Aware Learning Techniques and Trends in Cybersecurity
  • Author : Prithviraj Dasgupta,Joseph B. Collins,Ranjeev Mittu
  • Publisher : Springer Nature
  • Release : 22 January 2021
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This book is intended to give researchers and practitioners in the cross-cutting fields of artificial intelligence, machine learning (AI/ML) and cyber security up-to-date and in-depth knowledge of recent techniques for improving the vulnerabilities of AI/ML systems against attacks from malicious adversaries. The ten chapters in this book, written by eminent researchers in AI/ML and cyber-security, span diverse, yet inter-related topics including game playing AI and game theory as defenses against attacks on AI/ML systems, methods for

Deep Learning Fundamentals Theory and Applications

Deep Learning  Fundamentals  Theory and Applications
  • Author : Kaizhu Huang,Amir Hussain,Qiu-Feng Wang,Rui Zhang
  • Publisher : Springer
  • Release : 15 February 2019
GET THIS BOOK Deep Learning Fundamentals Theory and Applications

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

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 : 07 October 2020
GET THIS BOOK Artificial Intelligence Trends for Data Analytics Using Machine Learning and Deep Learning Approaches

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

"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.

The Development of Deep Learning Technologies

The Development of Deep Learning Technologies
  • Author : China Info & Comm Tech Grp Corp
  • Publisher : Springer Nature
  • Release : 13 July 2020
GET THIS BOOK The Development of Deep Learning Technologies

This book is a part of the Blue Book series “Research on the Development of Electronic Information Engineering Technology in China,” which explores the cutting edge of deep learning studies. A subfield of machine learning, deep learning differs from conventional machine learning methods in its ability to learn multiple levels of representation and abstraction by using several layers of nonlinear modules for feature extraction and transformation. The extensive use and huge success of deep learning in speech, CV, and NLP

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

The Development of Deep Learning Technologies

The Development of Deep Learning Technologies
  • Author : Chinese Academy of Engineering
  • Publisher : Springer
  • Release : 14 August 2020
GET THIS BOOK The Development of Deep Learning Technologies

This book is a part of the Blue Book series “Research on the Development of Electronic Information Engineering Technology in China,” which explores the cutting edge of deep learning studies. A subfield of machine learning, deep learning differs from conventional machine learning methods in its ability to learn multiple levels of representation and abstraction by using several layers of nonlinear modules for feature extraction and transformation. The extensive use and huge success of deep learning in speech, CV, and NLP

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
GET THIS BOOK Handbook of Research on Emerging Trends and Applications of Machine Learning

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.

AI and Deep Learning in Biometric Security

AI and Deep Learning in Biometric Security
  • Author : Gaurav Jaswal,Vivek Kanhangad,Raghavendra Ramachandra
  • Publisher : CRC Press
  • Release : 22 March 2021
GET THIS BOOK AI and Deep Learning in Biometric Security

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

Deep Learning in Biomedical and Health Informatics

Deep Learning in Biomedical and Health Informatics
  • Author : M. A. Jabbar,Ajith Abraham,Onur Dogan,Ana Maria Madureira,Sanju Tiwari
  • Publisher : CRC Press
  • Release : 27 September 2021
GET THIS BOOK Deep Learning in Biomedical and Health Informatics

This book provides a proficient guide on the relationship between Artificial Intelligence (AI) and healthcare and how AI is changing all aspects of the healthcare industry. It also covers how deep learning will help in diagnosis and the prediction of disease spread. The editors present a comprehensive review of research applying deep learning in health informatics in the fields of medical imaging, electronic health records, genomics, and sensing, and highlights various challenges in applying deep learning in health care. This