Trends in Deep Learning Methodologies Books

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Trends in Deep Learning Methodologies


Trends in Deep Learning Methodologies
  • Author : Vincenzo Piuri
  • Publisher : Academic Press
  • Release : 2020-12-01
  • ISBN : 9780128232682
  • Language : En, Es, Fr & De
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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
  • Publisher : CRC Press
  • Release : 2020-10-08
  • ISBN : 9781000179538
  • Language : En, Es, Fr & De
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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 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


Deep Learning
  • Author : Li Deng
  • Publisher :
  • Release : 2014
  • ISBN : 1601988141
  • Language : En, Es, Fr & De
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Provides an overview of general deep learning methodology and its applications to a variety of signal and information processing tasks

Handbook of Research on Deep Learning Innovations and Trends


Handbook of Research on Deep Learning Innovations and Trends
  • Author : Aboul Ella Hassanien
  • Publisher :
  • Release : 2019
  • ISBN : 1522578625
  • Language : En, Es, Fr & De
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"This book explores the application of deep learning in various areas like computer vision, image processing, biometrics, pattern recognition and medical imaging, and other real-world applications"--

Deep Learning Fundamentals Theory and Applications


Deep Learning  Fundamentals  Theory and Applications
  • Author : Kaizhu Huang
  • Publisher : Springer
  • Release : 2019-02-15
  • ISBN : 9783030060732
  • Language : En, Es, Fr & De
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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.