Appropriateness of Numbers of Receptive Fields in Convolutional Neural Networks Based on Classifying CIFAR-10 and EEACL26 Datasets
The topical question studied in this paper is how many receptive fields (filters) a convolutional layer of a convolutional neural network should have. The goal is to find a rule for choosing the most appropriate numbers of filters. The benchmark datasets are principally diverse CIFAR-10 and EEACL26...
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Format: | Article |
Language: | English |
Published: |
Sciendo
2018-12-01
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Series: | Electrical, Control and Communication Engineering |
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Online Access: | https://doi.org/10.2478/ecce-2018-0019 |