Optimization of the YOLOv5 deep learning model for peripheral blood cell detection and recognition-Reference-Cited by-同舟云学术

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Optimization of the YOLOv5 deep learning model for peripheral blood cell detection and recognition

Published:2024-01-26 Issue: Volume:4 Page:401-407
ISSN:
Container-title:Proceedings of the 2024 4th International Conference on Bioinformatics and Intelligent Computing
language:
Short-container-title:

Author:

Gao Yunfei¹^ORCID,Liu Yanhong¹^ORCID,Zhao Shilei¹^ORCID,Ma Xingxing¹^ORCID,Zhou Yun¹^ORCID

Affiliation:

1. Baotou Medical College, Inner Mongolia University of Science and Technology, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3665689.3665756

Reference24 articles.

1. Counting of WBCs and RBCs from blood images using gray thresholding;Patil P. R.;International Journal of Research in Engineering and Technology,2014

2. Learning to Detect Cells Using Non-overlapping Extremal Regions

3. Cell Detection From Redundant Candidate Regions Under Nonoverlapping Constraints

4. A GUI system for blood cell detection and recognition based on YOLOv5;Huang X.;Journal of Medical Artificial Intelligence,2020

5. A GUI system for blood cell detection and recognition based on YOLOv5;Chen H.;Medical News,2020

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