2024
DOI: 10.1117/1.jei.33.2.023046
|View full text |Cite
|
Sign up to set email alerts
|

Self-transformation of encoded subregion image data augmentation for better classification

Shicai Huang,
Jing Zhang,
Xue Deng

Abstract: Data augmentation has been proven to be an effective regularization strategy that can reduce over-fitting risks in deep learning models. Erasure based data augmentation is one of the most advanced solutions; however, random region erasure inevitably leads to excessive loss of object information and the introduction of a large amount of negative noise. In this work, a data augmentation method based on self-transformation of encoded image subregions is proposed. This method first designs an encoding mechanism ba… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Publication Types

Select...

Relationship

0
0

Authors

Journals

citations
Cited by 0 publications
references
References 29 publications
(36 reference statements)
0
0
0
Order By: Relevance

No citations

Set email alert for when this publication receives citations?