Evaluation of training datasets for typical target detection networks

Ziyu Xiao; Yuhang Wan; Weidong Yang

doi:10.1117/12.2692648

7 March 2024 Evaluation of training datasets for typical target detection networks

Ziyu Xiao, Yuhang Wan, Weidong Yang

Proceedings Volume 13086, MIPPR 2023: Pattern Recognition and Computer Vision; 130860E (2024) https://doi.org/10.1117/12.2692648
Event: Twelfth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2023), 2023, Wuhan, China

Abstract

Deep learning technology has been widely applied in the field of image object detection, and many mature object detection models have emerged, which rely on a large number of data samples for learning and training. However, in many practical application scenarios, it is difficult to obtain a large number of correctly labeled samples. The demand for the quantity and quality of training dataset samples is an important issue in the field of few-shot detection. This paper explores the relationship between sample size and training effectiveness through model training experiments on different datasets. It is found that the accuracy and recall of the model both above 70% when the sample size is more than 500, and less than 10% when the sample size is less than 100. We optimized a dataset of 197 images based on data augmentation, achieving an improvement in training effectiveness by increase 17.1% mean average precision of the model. By adjusting the simulation azimuth and pitch angles to obtain datasets with different sparsity, we trained the detection model using these datasets and tested the model's detection performance using test images. We found that increasing the shooting angle interval would make the dataset sparser, resulting in a decrease in the mean average precision of the model on the validation set and a decrease in the detection performance on the test images. Moreover, an overly sparse dataset could cause over-fitting problems.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Ziyu Xiao, Yuhang Wan, and Weidong Yang "Evaluation of training datasets for typical target detection networks", Proc. SPIE 13086, MIPPR 2023: Pattern Recognition and Computer Vision, 130860E (7 March 2024); https://doi.org/10.1117/12.2692648

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

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
8 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Education and training

Object detection

Data modeling

Target detection

Detection and tracking algorithms

Statistical modeling

Performance modeling

Show All Keywords

Keywords/Phrases

Search In:

Publication Years