SW-YOLO: improved YOLOv5s algorithm for blood cell detection

Yonglin Wu, Yinfeng Fang, Dongxu Gao, Hongwei Gao, Zhaojie Ju

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes an improved target detection algorithm SW-YOLO based on the YOLOv5s framework to solve the problems of low detection accuracy, wrong detection and missed detection in blood cell detection tasks. To begin with, the end of the backbone network is fused with Swin Transformer to improve network feature extraction. Next, since blood cells are mostly small and medium-sized targets, resulting in poor detection of large cells, the network layer that identifies large cells is removed. In addition, the normal convolution in the PANet network is replaced with depth-separable convolution during the feature fusion process to ensure the accuracy and real-time detection while having better detection results for small targets. At last, the loss function of the prediction layer uses EIOU to solve the positive and negative sample imbalance problem of CIOU. Compared with existing target detection algorithms such as Faster-RCNN, YOLOv4 and YOLOv5s, SW-YOLO improves to 99.5%, 95.3% and 93.3% mAP on the blood cell dataset BCCD for white blood cells, red blood cells and platelets respectively. The experimental results are eximious and the algorithm is highly practical for blood cell detection.
Original languageEnglish
Title of host publicationIntelligent Robotics and Applications 16th International Conference, ICIRA 2023, Hangzhou, China, July 5–7, 2023, Proceedings, Part III
EditorsHuayong Yang, Honghai Liu, Jun Zou, Zhouping Yin, Lianqing Liu, Geng Yang, Xiaoping Ouyang, Zhiyong Wang
PublisherSpringer
Pages161-172
Number of pages12
ISBN (Electronic)9789819964895
ISBN (Print)9789819964888
DOIs
Publication statusPublished - 11 Oct 2023
EventInternational Conference on Intelligent Robotics and Applications - Hangzhou, China
Duration: 5 Jul 20237 Jul 2023

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume14269
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349
NameLecture Notes in Artificial Intelligence
PublisherSpringer
ISSN (Print)2945-9133
ISSN (Electronic)2945-9141

Conference

ConferenceInternational Conference on Intelligent Robotics and Applications
Country/TerritoryChina
CityHangzhou
Period5/07/237/07/23

Keywords

  • blood cells testing
  • Swin Transformer
  • PAN
  • EIOU

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