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Deep Learning


Author : Ian Goodfellow
language : en
Publisher: MIT Press
Release Date : 2016-11-18



Download Deep Learning written by Ian Goodfellow and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-18 with Computers categories.


An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives.

Deep Learning


Author : Stellan Ohlsson
language : en
Publisher: Cambridge University Press
Release Date : 2011-01-31



Download Deep Learning written by Stellan Ohlsson and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-01-31 with Psychology categories.


Although the ability to retain, process, and project prior experience onto future situations is indispensable, the human mind also possesses the ability to override experience and adapt to changing circumstances. Cognitive scientist Stellan Ohlsson analyzes three types of deep, non-monotonic cognitive change: creative insight, adaptation of cognitive skills by learning from errors, and conversion from one belief to another, incompatible belief. For each topic, Ohlsson summarizes past research, re-formulates the relevant research questions, and proposes information-processing mechanisms that answer those questions. The three theories are based on the principles of redistribution of activation, specialization of practical knowledge, and re-subsumption of declarative information. Ohlsson develops the implications of those mechanisms by scaling their effects with respect to time, complexity, and social interaction. The book ends with a unified theory of non-monotonic cognitive change that captures the abstract properties that the three types of change share.

Automatic Speech Recognition


Author : Dong Yu
language : en
Publisher: Springer
Release Date : 2014-11-11



Download Automatic Speech Recognition written by Dong Yu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-11 with Technology & Engineering categories.


This book provides a comprehensive overview of the recent advancement in the field of automatic speech recognition with a focus on deep learning models including deep neural networks and many of their variants. This is the first automatic speech recognition book dedicated to the deep learning approach. In addition to the rigorous mathematical treatment of the subject, the book also presents insights and theoretical foundation of a series of highly successful deep learning models.

Deep Learning And Data Labeling For Medical Applications


Author : Gustavo Carneiro
language : en
Publisher: Springer
Release Date : 2016-10-07



Download Deep Learning And Data Labeling For Medical Applications written by Gustavo Carneiro and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-07 with Computers categories.


This book constitutes the refereed proceedings of two workshops held at the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016, in Athens, Greece, in October 2016: the First Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2016, and the Second International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2016. The 28 revised regular papers presented in this book were carefully reviewed and selected from a total of 52 submissions. The 7 papers selected for LABELS deal with topics from the following fields: crowd-sourcing methods; active learning; transfer learning; semi-supervised learning; and modeling of label uncertainty.The 21 papers selected for DLMIA span a wide range of topics such as image description; medical imaging-based diagnosis; medical signal-based diagnosis; medical image reconstruction and model selection using deep learning techniques; meta-heuristic techniques for fine-tuning parameter in deep learning-based architectures; and applications based on deep learning techniques.

Deep Learning For Medical Image Analysis


Author : S. Kevin Zhou
language : en
Publisher: Academic Press
Release Date : 2017-01-18



Download Deep Learning For Medical Image Analysis written by S. Kevin Zhou and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-18 with Technology & Engineering categories.


Deep learning is providing exciting solutions for medical image analysis problems and is seen as a key method for future applications. This book gives a clear understanding of the principles and methods of neural network and deep learning concepts, showing how the algorithms that integrate deep learning as a core component have been applied to medical image detection, segmentation and registration, and computer-aided analysis, using a wide variety of application areas. Deep Learning for Medical Image Analysis is a great learning resource for academic and industry researchers in medical imaging analysis, and for graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis. Covers common research problems in medical image analysis and their challenges Describes deep learning methods and the theories behind approaches for medical image analysis Teaches how algorithms are applied to a broad range of application areas, including Chest X-ray, breast CAD, lung and chest, microscopy and pathology, etc. Includes a Foreword written by Nicholas Ayache

Facilitating Deep Learning


Author : Julian Hermida
language : en
Publisher: CRC Press
Release Date : 2014-07-01



Download Facilitating Deep Learning written by Julian Hermida and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-01 with Business & Economics categories.


Deep learning is a committed approach to learning. It is a process of constructing and interpreting new knowledge in light of prior cognitive structures and experiences, which can be applied in new, unfamiliar contexts. Deep learning produces learning that lasts a lifetime; and it results in better quality learning and profound understanding. In contrast, surface learning involves a dispassionate approach to learning. The surface learner is not concerned with understanding. Information acquired is usually lost after examinations; and there is no profound understanding or knowledge construction. Research studies show that most university and college students today take a surface approach to learning. The purpose of this book is to show readers how to create a learning environment that promotes deep learning in their classes. The book will do so by providing readers with the theoretical and pedagogical tools needed to: • Understand the notion of deep learning • Design and implement courses that encourage students to take a deep approach to learning • Design engaging and innovative teaching and learning activities that encourage students to use higher-order cognitive skills to construct knowledge and negotiate meaning • Implement assessment tools aimed at facilitating the deep learning process • Support international and other nontraditional students to construct learning deeply. The book begins with an examination of the big picture: the institutional constraints that hinder a culture of deep learning. From there, it deconstructs the concept of deep learning, and it examines every element of the deep learning process. It also discusses the factors that contribute to produce a deep learning environment. The rest of the chapters are about how to facilitate deep learning. The book examines every component of the teaching and learning system: goals, performances, and evaluation. It discusses strategies and methods that teachers can adopt to help students learn how to read and write in their disciplines in a deep way. The book also discusses the notion of inclusive deep learning environments which focus on engaging nontraditional students.

Fundamentals Of Deep Learning


Author : Nikhil Buduma
language : en
Publisher:
Release Date : 2017-04



Download Fundamentals Of Deep Learning written by Nikhil Buduma and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04 with Computers categories.


With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research that is paving the way for modern machine learning. This book uses exposition and examples to help you understand major concepts in this complicated field. Large companies such as Google, Microsoft, and Facebook have taken notice, and are actively growing in-house deep learning teams. For the rest of us however, deep learning is still a pretty complex and difficult subject to grasp. If you have a basic understanding of what machine learning is, have familiarity with the Python programming language, and have some mathematical background with calculus, this book will help you get started.