A Particle Swarm Optimization-Based Flexible Convolutional Autoencoder for Image Classification

Convolutional autoencoders (CAEs) have shown their remarkable performance in stacking to deep convolutional neural networks (CNNs) for classifying image data during the past several years. However, they are unable to construct the state-of-the-art CNNs due to their intrinsic architectures. In this r...

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Veröffentlicht in:	IEEE transaction on neural networks and learning systems Jg. 30; H. 8; S. 2295 - 2309
Hauptverfasser:	Sun, Yanan, Xue, Bing, Zhang, Mengjie, Yen, Gary G.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.08.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Artificial neural networks Classification Computer applications Computer architecture Convolution Convolutional autoencoder (CAE) Convolutional codes deep learning Image classification Neural networks Optimization Particle swarm optimization particle swarm optimization (PSO) Stacking
ISSN:	2162-237X, 2162-2388, 2162-2388
Online-Zugang:	Volltext
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