文献类型： 外文期刊
作者： Liu, Guoqi 1 ; Zhao, Manqi 1 ; Bai, Lu 1 ; Zang, Hecang 2 ; Chang, Baofang 1 ;
作者机构： 1.Henan Normal Univ, Coll Comp & Informat Engn, Xinxiang 453007, Henan, Peoples R China
2.Henan Acad Agr Sci, Inst Agr Econ & Informat, Zhengzhou 450002, Henan, Peoples R China
关键词： Road extraction; CNN; Segmentation
期刊名称：JOURNAL OF SPATIAL SCIENCE （ 影响因子：1.84； 五年影响因子：1.946 ）
ISSN： 1449-8596
年卷期：
页码：
收录情况： SCI
摘要： Nowdays, many methods based on CNN have been proposed for road extraction. However, there are still great challenges. Therefore, according to image characteristics, this paper made corresponding improvements based on medical segmentation network PraNet. First, the reverse attention module (RA) connected at the last layer of PraNet is changed to the positive attention module (PA). Then, the negative matrix L1 norm regularization is added into the loss function. We conducted experiments on a data set made by UAV in the field of Henan Academy of Agricultural Sciences. The results show that the proposed method is better than the comparison models.
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