Handbook of Deep Learning Applications

Author:   Valentina Emilia Balas ,  Sanjiban Sekhar Roy ,  Dharmendra Sharma ,  Pijush Samui
Publisher:   Springer Nature Switzerland AG
Edition:   1st ed. 2019
Volume:   136
ISBN:  

9783030114787


Pages:   383
Publication Date:   06 March 2019
Format:   Hardback
Availability:   Manufactured on demand   Availability explained
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Handbook of Deep Learning Applications


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Overview

This book presents a broad range of deep-learning applications related to vision, natural language processing, gene expression, arbitrary object recognition, driverless cars, semantic image segmentation, deep visual residual abstraction, brain–computer interfaces, big data processing, hierarchical deep learning networks as game-playing artefacts using regret matching, and building GPU-accelerated deep learning frameworks. Deep learning, an advanced level of machine learning technique that combines class of learning algorithms with the use of many layers of nonlinear units, has gained considerable attention in recent times. Unlike other books on the market, this volume addresses the challenges of deep learning implementation, computation time, and the complexity of reasoning and modeling different type of data. As such, it is a valuable and comprehensive resource for engineers, researchers, graduate students and Ph.D. scholars.

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Author:   Valentina Emilia Balas ,  Sanjiban Sekhar Roy ,  Dharmendra Sharma ,  Pijush Samui
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
Edition:   1st ed. 2019
Volume:   136
Weight:   0.752kg
ISBN:  

9783030114787


ISBN 10:   3030114783
Pages:   383
Publication Date:   06 March 2019
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

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