Completely Automated CNN Architecture Design Based on Blocks

The performance of convolutional neural networks (CNNs) highly relies on their architectures. In order to design a CNN with promising performance, extensive expertise in both CNNs and the investigated problem domain is required, which is not necessarily available to every interested user. To address...

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Bibliographic Details
Published in:	IEEE transaction on neural networks and learning systems Vol. 31; no. 4; pp. 1242 - 1254
Main Authors:	Sun, Yanan, Xue, Bing, Zhang, Mengjie, Yen, Gary G.
Format:	Journal Article
Language:	English
Published:	United States IEEE 01.04.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Artificial neural networks Automatic architecture design Classification Competition Computer applications Computer architecture convolutional neural networks (CNNs) Domains Encoding Evolutionary computation evolutionary deep learning Genetic algorithms genetic algorithms (GAs) Neural networks Optimization Sociology Statistics User requirements
ISSN:	2162-237X, 2162-2388, 2162-2388
Online Access:	Get full text
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