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...
Saved in:
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Riga Technical University Press
2018-12-01
|
| Series: | Electrical, Control and Communication Engineering |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/ecce-2018-0019 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|