A review of deep learning dataset construction and model application based on microbial imaging
10.3760/cma.j.cn114452-20240718-00385
- VernacularTitle:基于微生物图像的深度学习数据集构建与模型应用研究
- Author:
Jia DU
1
;
Jiancheng XU
;
Qi ZHOU
;
Ze LI
;
Xuewen LI
Author Information
1. 吉林大学第一医院检验科，长春130021
- Publication Type:Journal Article
- Keywords:
Deep learning;
Pathogenic microorganism;
Image analysis;
Image capture;
Neural network model
- From:
Chinese Journal of Laboratory Medicine
2025;48(2):280-285
- CountryChina
- Language:Chinese
-
Abstract:
With the rapid development of computer vision technology, deep learning models have demonstrated new research area and potential value in intelligent microbiological detection. By utilizing multilayer neural networks and large amounts of training data, these models are capable of automated extraction and analysis for complex features, thereby improving the efficiency and accuracy of detection. This paper introduces the research background of deep learning in microbiological image detection, and elaborates on the methods for constructing microbiological image datasets, including data collection, preprocessing, annotation, and partitioning, and introduces typical deep learning models as well as their application examples in various microbiological detection. Deep learning in microbiological image analysis faces numerous challenges which needs further development.
