YOLOv5-DCN: An Effective Improvement Based on YOLOv5 Detector
International Journal of Computer Science and Information Technology, (2024), Vol.4, No.3, pp.31-35
Published: November 24, 2024
Abstract
Urine sediment detection is of great significance for the diagnosis and monitoring of kidney diseases, urinary tract infections, stones, etc. This study aims to propose fast, high-precision and lightweight Urinary particles detection model based on YOLOv5, deformable convolution, and evaluate its performance in Urinary particles detection tasks.
Keywords:
Urine Sediment, YOLOv5, Deformable Convolution
APA Citation:
Xiaoxia Qi, Md Gapar Md Johar, Ali Khatibi, Jacquline Tham, Long Cheng (2024). YOLOv5-DCN: An Effective Improvement Based on YOLOv5 Detector. International Journal of Computer Science and Information Technology, 4(3), 31-35. https://doi.org/10.62051/ijcsit.v4n3.04
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