Innovative Topologies and Algorithms for Neural Networks
The introduction of new topologies and training procedures to deep neural networks has solicited a renewed interest in the field of neural computation. The use of deep structures has significantly improved state-of-the-art applications in many fields, such as computer vision, speech and text process...
Main Author: | |
---|---|
Other Authors: | |
Format: | eBook |
Language: | English |
Published: |
Basel, Switzerland
MDPI - Multidisciplinary Digital Publishing Institute
2021
|
Subjects: | |
Online Access: | |
Collection: | Directory of Open Access Books - Collection details see MPG.ReNa |
Summary: | The introduction of new topologies and training procedures to deep neural networks has solicited a renewed interest in the field of neural computation. The use of deep structures has significantly improved state-of-the-art applications in many fields, such as computer vision, speech and text processing, medical applications, and IoT (Internet of Things). The probability of a successful outcome from a neural network is linked to selection of an appropriate network architecture and training algorithm. Accordingly, much of the recent research on neural networks has been devoted to the study and proposal of novel architectures, including solutions tailored to specific problems. This book gives significant contributions to the above-mentioned fields by merging theoretical aspects and relevant applications. |
---|---|
Item Description: | Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/ |
Physical Description: | 1 electronic resource (198 p.) |
ISBN: | books978-3-0365-0285-4 9783036502854 9783036502847 |