CIOMP OpenIR
Semantic segmentation based on DeepLabV3+ and superpixel optimization
F.-L.Ren; X.He; Z.-H.Wei; Y.Lu; M.-Y.Li
2019
发表期刊Guangxue Jingmi Gongcheng/Optics and Precision Engineering
ISSN1004924X
卷号27期号:12页码:2722-2729
摘要To tackle the problem where by DeepLabV3+ loses considerable detail information during feature extraction, which leads to poor segmentation results in the edges of the objects, this study proposed a semantics segmentation algorithm based on DeepLabV3+ and optimized by superpixels. First, a DeepLabV3+ model was chosen to extract semantic features and obtain coarse semantic segmentation results. Then, the simple linear iterative clustering algorithm was used to segment the input image into superpixels. Finally, high-level abstract semantic features and detailed information of the superpixels were fused to obtain edge optimized semantic segmentation results. Experiments conducted on the PASCAL VOC 2O12 dataset show that compared to DeepLabV3+, the proposed algorithm had superior performance in terms of detail parts such as edges of objects, and the value of mIoU reached 83.8%.The proposed algorithm thus outperformed other state-of-the-art algorithms in terms of semantic segmentation. 2019, Science Press. All right reserved.
关键词Image segmentation,Clustering algorithms,Deep learning,Iterative methods,Semantics,Superpixels
DOI10.3788/OPE.20192712.2722
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收录类别EI
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文献类型期刊论文
条目标识符http://ir.ciomp.ac.cn/handle/181722/63094
专题中国科学院长春光学精密机械与物理研究所
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GB/T 7714
F.-L.Ren,X.He,Z.-H.Wei,et al. Semantic segmentation based on DeepLabV3+ and superpixel optimization[J]. Guangxue Jingmi Gongcheng/Optics and Precision Engineering,2019,27(12):2722-2729.
APA F.-L.Ren,X.He,Z.-H.Wei,Y.Lu,&M.-Y.Li.(2019).Semantic segmentation based on DeepLabV3+ and superpixel optimization.Guangxue Jingmi Gongcheng/Optics and Precision Engineering,27(12),2722-2729.
MLA F.-L.Ren,et al."Semantic segmentation based on DeepLabV3+ and superpixel optimization".Guangxue Jingmi Gongcheng/Optics and Precision Engineering 27.12(2019):2722-2729.
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