Multidimensional attention and multiscale upsampling for semantic segmentationOACSCD
Semantic segmentation is for pixel-level classification tasks,and contextual information has an important impact on the performance of segmentation.In order to capture richer contextual information,we adopt ResNet as the back…查看全部>>
LU Zhongda;ZHANG Chunda;WANG Lijing;XU Fengxia
School of Mechanical and Electrical Engineering, Qiqihar University, Qiqihar 161000, China Heilongjiang Province Collaborative Innovation Center for Intelligent Manufacturing Equipment Industrialization, Qiqihar 161000, ChinaSchool of Mechanical and Electrical Engineering, Qiqihar University, Qiqihar 161000, China Heilongjiang Province Collaborative Innovation Center for Intelligent Manufacturing Equipment Industrialization, Qiqihar 161000, ChinaSchool of Mechanical and Electrical Engineering, Qiqihar University, Qiqihar 161000, China Heilongjiang Province Collaborative Innovation Center for Intelligent Manufacturing Equipment Industrialization, Qiqihar 161000, ChinaSchool of Mechanical and Electrical Engineering, Qiqihar University, Qiqihar 161000, China Heilongjiang Province Collaborative Innovation Center for Intelligent Manufacturing Equipment Industrialization, Qiqihar 161000, China
计算机与自动化
semantic segmentationattention mechanismmultiscale featureconvolutional neural network(CNN)residual network(ResNet)
《测试科学与仪器：英文版》 2022 (1)
P.68-78,11
Fundamental Research Fund in Heilongjiang Provincial Universities(Nos.135409602,135409102)。
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