Trends in Deep Learning Methodologies

Written By Vincenzo Piuri
Trends in Deep Learning Methodologies
  • Publsiher : Academic Press
  • Release : 12 November 2020
  • ISBN : 0128232684
  • Pages : 306 pages
  • Rating : 4/5 from 21 reviews
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Read or download book entitled Trends in Deep Learning Methodologies written by Vincenzo Piuri which was release on 12 November 2020, this book published by Academic Press. Available in PDF, EPUB and Kindle Format. Book 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

Trends in Deep Learning Methodologies

Trends in Deep Learning Methodologies
  • Author : Vincenzo Piuri,Sandeep Raj,Angelo Genovese,Rajshree Srivastava
  • Publisher : Academic Press
  • Release Date : 2020-11-12
  • Total pages : 306
  • ISBN : 0128232684
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Summary : 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 ...

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 Date : 2021-12-31
  • Total pages : 328
  • ISBN : 0128232684
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Summary : 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 ...

Deep Learning for Personalized Healthcare Services

Deep Learning for Personalized Healthcare Services
  • Author : Vishal Jain,Jyotir Moy Chatterjee,Hadi Hedayati,Salahddine Krit,Omer Deperlioglu
  • Publisher : Walter de Gruyter GmbH & Co KG
  • Release Date : 2021-10-25
  • Total pages : 268
  • ISBN : 0128232684
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Summary : 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 ...

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 Date : 2009-08-31
  • Total pages : 852
  • ISBN : 0128232684
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Summary : "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 Date : 2020-10-17
  • Total pages : 998
  • ISBN : 0128232684
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Summary : 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 ...

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 Date : 2021-09-14
  • Total pages : 296
  • ISBN : 0128232684
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Summary : 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 ...

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 Date : 2022-02-08
  • Total pages : 294
  • ISBN : 0128232684
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Summary : 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 ...

Trends and Applications of Text Summarization Techniques

Trends and Applications of Text Summarization Techniques
  • Author : Fiori, Alessandro
  • Publisher : IGI Global
  • Release Date : 2019-08-30
  • Total pages : 335
  • ISBN : 0128232684
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Summary : 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. ...

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 Date : 2020-10-07
  • Total pages : 250
  • ISBN : 0128232684
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Summary : 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 ...

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 Date : 2021-09-22
  • Total pages : 216
  • ISBN : 0128232684
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Summary : 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 ...

Explainable Artificial Intelligence for Smart Cities

Explainable Artificial Intelligence for Smart Cities
  • Author : Mohamed Lahby,Utku Kose,Akash Kumar Bhoi
  • Publisher : CRC Press
  • Release Date : 2021-11-10
  • Total pages : 360
  • ISBN : 0128232684
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Summary : 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 ...

Advanced Biometrics with Deep Learning

Advanced Biometrics with Deep Learning
  • Author : Andrew Teoh Beng Jin ,Lu Leng
  • Publisher : MDPI
  • Release Date : 2020-12-28
  • Total pages : 210
  • ISBN : 0128232684
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Summary : Biometrics, such as fingerprint, iris, face, hand print, hand vein, speech and gait recognition, etc., as a means of identity management have become commonplace nowadays for various applications. Biometric systems follow a typical pipeline, that is composed of separate preprocessing, feature extraction and classification. Deep learning as a data-driven representation ...

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 Date : 2021-09-26
  • Total pages : 224
  • ISBN : 0128232684
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Summary : 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 ...

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 Date : 2020-10-08
  • Total pages : 266
  • ISBN : 0128232684
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Summary : 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 ...

Deep Learning for Time Series Forecasting

Deep Learning for Time Series Forecasting
  • Author : Jason Brownlee
  • Publisher : Machine Learning Mastery
  • Release Date : 2018-08-30
  • Total pages : 575
  • ISBN : 0128232684
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Summary : Deep learning methods offer a lot of promise for time series forecasting, such as the automatic learning of temporal dependence and the automatic handling of temporal structures like trends and seasonality. With clear explanations, standard Python libraries, and step-by-step tutorial lessons you’ll discover how to develop deep learning models ...