Handbook of Deep Learning Applications

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 d...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Balas, Valentina Emilia (Editor), Roy, Sanjiban Sekhar (Editor), Sharma, Dharmendra (Editor), Samui, Pijush (Editor)
Format: e-Book
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2019.
Edition:1st ed. 2019.
Series:Smart Innovation, Systems and Technologies, 136
Subjects:
Computational intelligence.
Artificial intelligence.
Signal processing.
Neural networks (Computer science) .
Data mining.
Computational Intelligence.
Artificial Intelligence.
Signal, Speech and Image Processing.
Mathematical Models of Cognitive Processes and Neural Networks.
Data Mining and Knowledge Discovery.
Online Access:Full-text access
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Table of Contents:
  • Designing a Neural Network from scratch for Big Data powered by Multi-node GPUs
  • Deep Learning for Scene Understanding
  • Deep Learning for Driverless Vehicles
  • Deep Learning for Document Representation
  • Deep learning for marine species recognition
  • Deep molecular representation in Cheminformatics
  • Deep Learning in eHealth
  • Deep Learning for Brain Computer Interfaces
  • Deep Learning in Gene Expression Modeling.

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