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Trends in Deep Learning Methodologies

Trends in Deep Learning Methodologies: Algorithms, Applications, and Systems covers deep learning approaches such as neural networks, deep;

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Deep Learning in Biometrics

Deep Learning is now synonymous with applied machine learning. Many technology giants (e.g. Google, Microsoft, Apple, IBM) as well as start;

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Deep Learning

describe how many deep learning methodologies have brought great breakthroughs in various applications of text, image, video, speech and audio;

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The Development of Deep Learning Technologies

explores the cutting edge of deep learning studies. A subfield of machine learning, deep learning differs from conventional machine learning;

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Applied Deep Learning and Computer Vision for Self-Driving Cars

This book teaches you the different techniques and methodologies associated while implementing deep learning solutions in self-driving cars;

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Disruptive Trends in Computer Aided Diagnosis

learning methodologies on evolving accurate and precise early detection and medical diagnosis systems. Information presented in an;

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The International Conference on Deep Learning, Big Data and Blockchain (Deep-BDB 2021)

The role of deep learning for the analysis and learning of massive amounts of data from all aspects of daily-life has dramatically changed;

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A Simple Guide to Data Driven Technologies using Machine Learning and Deep Learning

If you are an active user of statistics to examine trends in your business, then using machine learning is your next best step. It uses;

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Recent Trends in Learning from Data: Tutorials from the Inns Big Data and Deep Learning Conference (Innsbddl2019)

This book offers a timely snapshot and extensive practical and theoretical insights into the topic of learning from data. Based on the;

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Advanced Deep Learning with Python

everything from how neural networks work to training CNN models. In this book, you'll discover newly developed deep learning models, methodologies;

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Deep Learning for Data Analytics

, biomedical engineering, and object tracking using deep learning methodologies. The book provides a pragmatic direction for researchers who wish to;

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Deep Learning Techniques for Biomedical and Health Informatics

Deep Learning Techniques for Biomedical and Health Informatics provides readers with the state-of-the-art in deep learning-based;

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Deep Learning

This book introduces readers to the fundamental concepts of deep learning and offers practical insights into how this learning paradigm;

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Deep Learning: Concepts and Architectures

This book introduces readers to the fundamental concepts of deep learning and offers practical insights into how this learning paradigm;

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Recent Trends in Learning From Data

This book offers a timely snapshot and extensive practical and theoretical insights into the topic of learning from data. Based on the;

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Deep Learning Based Approaches for Sentiment Analysis

This book covers deep-learning-based approaches for sentiment analysis, a relatively new, but fast-growing research area, which has;

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Multi-disciplinary Trends in Artificial Intelligence

learning; deep learning and its applications; document analysis; intelligent information systems; swarm intelligence.;

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Deep Learning

, and driverless cars. Deep learning is an artificial intelligence technology that enables computer vision, speech recognition in mobile phones;

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Knowledge Management and E-Learning

begins by considering KM practices, techniques, and methodologies in e-learning. These chapters explain how knowledge capture, retention;

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Deep Learning Approaches to Cloud Security

DEEP LEARNING APPROACHES TO CLOUD SECURITY Covering one of the most important subjects to our society today, cloud security, this editorial;

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Machine Learning for Speaker Recognition

This book will help readers understand fundamental and advanced statistical models and deep learning models for robust speaker recognition;

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Deep Learning from the Basics: Python and Deep Learning

Discover ways to implement various deep learning algorithms by leveraging Python and other technologies Key Features Learn deep;

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Thinking Machines

Thinking Machines: Machine Learning and Its Hardware Implementation covers the theory and application of machine learning, neuromorphic;

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Deep Learning for Hyperspectral Image Analysis and Classification

This book focuses on deep learning-based methods for hyperspectral image (HSI) analysis. Unsupervised spectral-spatial adaptive band-noise;

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Deep Learning for Hyperspectral Image Analysis and Classification

This book focuses on deep learning-based methods for hyperspectral image (HSI) analysis. Unsupervised spectral-spatial adaptive band-noise;

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Blended Learning

with mobile and web-based learning environments. Blended Learning: Concepts, Methodologies, Tools, and Applications explores emerging trends;

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Image Fusion in Remote Sensing

deep learning approaches are covered. First, the conventional approaches to image fusion in remote sensing are discussed. These approaches;

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