research-article

SN-YOLO: Improved YOLOv5 with Softer-NMS and SIOU for Object Detection

Authors:

Zhen WangAuthors Info & Claims

AIPR '22: Proceedings of the 2022 5th International Conference on Artificial Intelligence and Pattern Recognition

Pages 326 - 330

https://doi.org/10.1145/3573942.3574029

Published: 16 May 2023 Publication History

Abstract

As a lightweight target detection network, YOLOv5 is popular in the industry for its advantages of fast speed and small model, but the detection accuracy is not very high. In response to this problem, we propose an improved model SN-YOLO based on YOLOv5. First, we introduce Softer-NMS as the post-processing method of the model, which will make the prediction box more accurate. Secondly, we improved the loss function of the original algorithm and introduced the SIOU loss function to optimize the model and improve the accuracy of the algorithm. Finally, in order to improve the feature extraction ability of the backbone, we implanted the CBAM (Convolutional block attention module) module into the algorithm. We validate the model using the 2007 and 2012 datasets of PASCAL VOC. The experimental results show that SN-YOLO has a great improvement over the original model in all aspects. The effectiveness of the algorithm is verified.

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Cited By

Sheng JShi DWang PGong X(2024)Traffic Sign Detection Algorithm Based on Improved YOLOv52024 17th International Conference on Advanced Computer Theory and Engineering (ICACTE)10.1109/ICACTE62428.2024.10871684(150-158)Online publication date: 13-Sep-2024
https://doi.org/10.1109/ICACTE62428.2024.10871684
Pan YZhang LZhang Y(2024)Rapid Detection of PCB Defects Based on YOLOx-Plus and FPGAIEEE Access10.1109/ACCESS.2024.338794712(61343-61358)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3387947
Cao ZLi ZFang LLi J(2024)Lightweight coal and gangue detection algorithm based on improved Yolov7-tinyInternational Journal of Coal Preparation and Utilization10.1080/19392699.2023.230130444:11(1773-1792)Online publication date: 4-Jan-2024
https://doi.org/10.1080/19392699.2023.2301304

Index Terms

SN-YOLO: Improved YOLOv5 with Softer-NMS and SIOU for Object Detection
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Object detection

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AIPR '22: Proceedings of the 2022 5th International Conference on Artificial Intelligence and Pattern Recognition

September 2022

1221 pages

ISBN:9781450396899

DOI:10.1145/3573942

Copyright © 2022 ACM.

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Publication History

Published: 16 May 2023

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Science Research Plan of the Shaanxi Provincial Department of Education

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AIPR 2022

AIPR 2022: 2022 5th International Conference on Artificial Intelligence and Pattern Recognition

September 23 - 25, 2022

Xiamen, China

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Cited By

Sheng JShi DWang PGong X(2024)Traffic Sign Detection Algorithm Based on Improved YOLOv52024 17th International Conference on Advanced Computer Theory and Engineering (ICACTE)10.1109/ICACTE62428.2024.10871684(150-158)Online publication date: 13-Sep-2024
https://doi.org/10.1109/ICACTE62428.2024.10871684
Pan YZhang LZhang Y(2024)Rapid Detection of PCB Defects Based on YOLOx-Plus and FPGAIEEE Access10.1109/ACCESS.2024.338794712(61343-61358)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3387947
Cao ZLi ZFang LLi J(2024)Lightweight coal and gangue detection algorithm based on improved Yolov7-tinyInternational Journal of Coal Preparation and Utilization10.1080/19392699.2023.230130444:11(1773-1792)Online publication date: 4-Jan-2024
https://doi.org/10.1080/19392699.2023.2301304

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