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A METHOD AND A SYSTEM TRAINING A MODEL TO PERFORM SEMANTIC SEGMENTATION ON FOGGY IMAGES

机译:一种方法和系统培训模型,以在有雾图像上执行语义分割

摘要

A system and a method for training a model to be used for semantic segmentation of images, comprising:a—obtaining (S01) a first plurality of foggy images (101),b—training (S02) a classification model for estimating fog density,c—classifying (S03) a second plurality of images (101) having light fog,d—obtaining (S04) a third plurality of foggy images (103) having light fog,e—training (S05) a semantic segmentation model using the third plurality of foggy images,f—applying (S06) the semantic segmentation model to the second plurality of foggy (102) images to obtain semantic segmentations (102′),g—obtaining (S07) a fourth plurality of foggy images (104) having dense fog,h—training (S08) using the previously obtained foggy images.
机译:用于训练用于用于图像语义分割的模型的系统和方法,包括: a-获取(s 01 )第一多个雾图像(< b> 101 ), b训练(s 02 )用于估计雾密度的分类模型, C-Scrousify(s 03 )具有光的第二多个图像( 101 )雾, D-获取(S 04 )第三多个雾图像( 103 )具有浅雾, 电子训练(s 05 )使用第三多个雾图像的语义分割模型, f申请(s 06 )对第二多个雾的语义分段模型( 102 )图像以获取语义分割( 102 '), g获取(s 07 )一个烦恼具有致密雾的Rth多个雾图像( 104 ), H训练(s 08 )使用先前获得的雾图像。

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