A grammar-based GP approach applied to the design of deep neural networks

Deep Learning has been very successful in automating the feature engineering process, widely applied for various tasks, such as speech recognition, classification, segmentation of images, time-series forecasting, among others. Deep neural networks (DNNs) incorporate the power to learn patterns throu...

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Bibliographic Details
Published in:	Genetic programming and evolvable machines Vol. 23; no. 3; pp. 427 - 452
Main Authors:	Lima, Ricardo H. R., Magalhães, Dimmy, Pozo, Aurora, Mendiburu, Alexander, Santana, Roberto
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.09.2022 Springer Nature B.V
Subjects:	Artificial Intelligence Artificial neural networks Biomedical Engineering and Bioengineering Compilers Computer Science Configuration management Electrical Engineering Evolutionary algorithms Genetic algorithms Image classification Image segmentation Interpreters Machine learning Neural networks Object recognition Programming Languages Programming Techniques Software Engineering/Programming and Operating Systems Special Issue: Highlights of Genetic Programming 2021 Events Speech recognition Grammatical evolution Automatic design Deep neural networks Evolutionary algorithms Genetic programming
ISSN:	1389-2576, 1573-7632
Online Access:	Get full text
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