A lightweight deep-learning model for parasite egg detection in microscopy images
Compared with the baseline model, YAC-Net optimizes the model structure and simplifies the parameters while ensuring the detection performance. It helps to reduce the equipment requirements for performing automated detection and can be used to realize the automatic detection of parasite eggs under microscope images.
Authors
- Qiang Zhai (ORCID: https://orcid.org/0000-0001-6587-6642)
- Jing Hua (ORCID: https://orcid.org/0000-0002-4715-3077)
- Jizhong Liu (ORCID: https://orcid.org/0000-0002-7658-5231)
- Wenbin Xu (ORCID: https://orcid.org/0000-0001-7168-3724)
- Xingyu Xu
Institutions
- Nanchang University (CN)
- Shaoxing University (CN)
- Wuhan University of Technology (CN)
- Jiangxi Agricultural University (CN)
Publication Details
- Journal
- Parasites & Vectors
- Published
- 2024-11-06
- DOI
- https://doi.org/10.1186/s13071-024-06503-2
- Citations
- 12
- Primary Topic
- Digital Imaging for Blood Diseases
- Type
- article
- Field-Weighted Citation Impact
- 2.99
Funders
- Natural Science Foundation of Jiangxi Province