@inproceedings{3cec02caa39947be965b924cfcd0f45b,
title = "Analyzing Early Stage Crassostrea Hongkongensis Embryos with Deep Learning",
abstract = "Crassostrea hongkongensis, is a representative bi-valve mollusk, which is one of the main aquaculture shellfish in China. Identifying different development stages of fertilized oyster eggs is of importance in its breeding. To facilitate oyster breeding, we utilize YOLOv11 as well as self-designed algorithms to evaluate oyster embryo development quantitatively and qualitatively. Experiment results indicate that these algorithms can save researchers' laborious efforts and enhance research efficiency.",
keywords = "YOLOv11, deep learning, embryo, morula stage, oyster",
author = "Fei Wang and Jiayao Sun and Xiangmeng Qu and Ke Huang and Jiangkangjian Chen",
note = "Publisher Copyright: {\textcopyright} 2026 IEEE.; 3rd International Conference on Digital Image Processing and Computer Applications, DIPCA 2026 ; Conference date: 24-04-2026 Through 26-04-2026",
year = "2026",
doi = "10.1109/DIPCA70202.2026.11565962",
language = "英语",
series = "2026 3rd International Conference on Digital Image Processing and Computer Applications, DIPCA 2026",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "168--172",
booktitle = "2026 3rd International Conference on Digital Image Processing and Computer Applications, DIPCA 2026",
address = "美国",
}