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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Bibliographic Details
Main Author: Romanuke Vadim
Format: Article
Language:English
Published: Sciendo 2018-12-01
Series:Electrical, Control and Communication Engineering
Subjects:
Online Access:https://doi.org/10.2478/ecce-2018-0019