Lightweight semantic segmentation network with configurable context and small object attention

doi:10.3389/fncom.2023.1280640

CIOMP OpenIR

	Lightweight semantic segmentation network with configurable context and small object attention
	C. Zhang, F. Xu, C. Wu and J. Li
	2023
发表期刊	Frontiers in Computational Neuroscience
ISSN	16625188
卷号	17
摘要	The current semantic segmentation algorithms suffer from encoding feature distortion and small object feature loss. Context information exchange can effectively address the feature distortion problem, but it has the issue of fixed spatial range. Maintaining the input feature resolution can reduce the loss of small object information but would slow down the network’s operation speed. To tackle these problems, we propose a lightweight semantic segmentation network with configurable context and small object attention (CCSONet). CCSONet includes a long-short distance configurable context feature enhancement module (LSCFEM) and a small object attention decoding module (SOADM). The LSCFEM differs from the regular context exchange module by configuring long and short-range relevant features for the current feature, providing a broader and more flexible spatial range. The SOADM enhances the features of small objects by establishing correlations among objects of the same category, avoiding the introduction of redundancy issues caused by high-resolution features. On the Cityscapes and Camvid datasets, our network achieves the accuracy of 76.9 mIoU and 73.1 mIoU, respectively, while maintaining speeds of 87 FPS and 138 FPS. It outperforms other lightweight semantic segmentation algorithms in terms of accuracy. Copyright © 2023 Zhang, Xu, Wu and Li.
DOI	10.3389/fncom.2023.1280640
URL	查看原文
收录类别	sci ; ei
引用统计
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/68149
专题	中国科学院长春光学精密机械与物理研究所
推荐引用方式 GB/T 7714	C. Zhang, F. Xu, C. Wu and J. Li. Lightweight semantic segmentation network with configurable context and small object attention[J]. Frontiers in Computational Neuroscience,2023,17.
APA	C. Zhang, F. Xu, C. Wu and J. Li.(2023).Lightweight semantic segmentation network with configurable context and small object attention.Frontiers in Computational Neuroscience,17.
MLA	C. Zhang, F. Xu, C. Wu and J. Li."Lightweight semantic segmentation network with configurable context and small object attention".Frontiers in Computational Neuroscience 17(2023).

条目包含的文件		下载所有文件
文件名称/大小	文献类型	版本类型	开放类型	使用许可
Lightweight semantic（3814KB）	期刊论文	出版稿	开放获取	CC BY-NC-SA	浏览下载