Optimization of convolutional neural networks for image classification using genetic algorithms and bayesian optimization

Optimization of convolutional neural networks for image classification using genetic algorithms and bayesian optimization

Notwithstanding the recent successes of deep convolutional neural networks for classification tasks, they are sensitive to the selection of their hyperparameters, which impose an exponentially large search space on modern convolutional models. Traditional hyperparameter selection methods include man...

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Bibliographic Details
Main Author: Rawat, Waseem
Other Authors: Wang, Zenghui
Format: Others
Language:en
Published: 2018
Subjects:
Deep learning
Artificial neural networks
Convolutional neural networks
Evolutionary algorithms
Genetic algorithms
Bayesian optimization
Computer vision
Image classification
Model selection
Hyperparameter optimization
006.32
Neural networks (Computer science)
Image processing > Digital techniques
Online Access:Rawat, Waseem (2018) Optimization of convolutional neural networks for image classification using genetic algorithms and bayesian optimization, University of South Africa, Pretoria, <http://hdl.handle.net/10500/24977>
http://hdl.handle.net/10500/24977

Internet

Rawat, Waseem (2018) Optimization of convolutional neural networks for image classification using genetic algorithms and bayesian optimization, University of South Africa, Pretoria, <http://hdl.handle.net/10500/24977>
http://hdl.handle.net/10500/24977

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