Dataset Reduction Algorithm Based on Deep Features Clustering

DOI

10.2991/978-94-6463-058-9_148How to use a DOI?

Keywords

Dataset reduction algorithm; Prototype selection; Deep features; Clustering

ABSTRACT

The dataset reduction algorithm is to obtain the simplified dataset through compressing original dataset based on a strategy and rule. It ensures to reduce the training set size as much as possible, without changing generalization ability of the simplified dataset. To study the algorithm with better reduction effect for deep learning image dataset, the paper introduces prototype selection, feature extraction and other concepts in dataset reduction; proposes the dataset reduction algorithm combined with deep feature extraction framework and clustering; and realizes effective reduction for deep learning image dataset. The experimental results indicate that the proposed reduction algorithm can effectively improve generalization of the image dataset with better effect than other similar reduction algorithms. Besides, the paper verifies validity of the algorithm.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Jian Tang
AU  - Hua Cheng
PY  - 2022
DA  - 2022/12/27
TI  - Dataset Reduction Algorithm Based on Deep Features Clustering
BT  - Proceedings of the 2nd International Conference on Internet, Education and Information Technology (IEIT 2022)
PB  - Atlantis Press
SP  - 948
EP  - 955
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-058-9_148
DO  - 10.2991/978-94-6463-058-9_148
ID  - Tang2022
ER  -