Small sample datasets build powerful image classification models

Junjie Wu

doi:10.1117/12.2640983

13 October 2022 Small sample datasets build powerful image classification models

Junjie Wu

Proceedings Volume 12287, International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2022); 122871V (2022) https://doi.org/10.1117/12.2640983
Event: International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2022), 2022, Wuhan, China

Abstract

Neural networks have been successfully applied in many fields. However, satisfactory results can only be obtained under large sample conditions. When it comes to small training sets, the performance may not be very good, or the learning task may not even be completed. In this study, our main task is to use data augmentation to solve the problems caused by small datasets. And we chose ImageDataGenerator in keras to obtain countless derived pictures for training. Also, we use the current state-of-the-art method, EfficientNet, to construct a classification model of different optimizers. The best model accuracy is 0.9647. Finally, we prove that EfficientNet is one of the most suitable methods for this study.

Citation Download Citation

Junjie Wu "Small sample datasets build powerful image classification models", Proc. SPIE 12287, International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2022), 122871V (13 October 2022); https://doi.org/10.1117/12.2640983

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available