Handbook of Deep Learning Applications

• Corporate Author: SpringerLink (Online service)
• Other Authors: Balas, Valentina Emilia (Editor, http://id.loc.gov/vocabulary/relators/edt), Roy, Sanjiban Sekhar (Editor, http://id.loc.gov/vocabulary/relators/edt), Sharma, Dharmendra (Editor, http://id.loc.gov/vocabulary/relators/edt), Samui, Pijush (Editor, http://id.loc.gov/vocabulary/relators/edt)
• Format: Electronic eBook
• 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.; Image processing.; Speech processing systems.; Neural networks (Computer science) .; Data mining.; Computational Intelligence.; Artificial Intelligence.; Signal, Image and Speech Processing.; Mathematical Models of Cognitive Processes and Neural Networks.; Data Mining and Knowledge Discovery.

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...

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.