Incorporating convolutional and transformer architectures to enhance semantic segmentation of fine-resolution urban images

Xizi Yua MOE Key Laboratory of Western China’s Environmental Systems, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, ChinaView further author information

Shuang Lib Guangzhou Urban Planning & Design Survey Research Institute, Guangzhou, China;c Collaborative Innovation Center for Natural Resources Planning and Marine Technology of Guangzhou, Guangzhou, China;d Guangdong Enterprise Key Laboratory for Urban Sensing, Monitoring and Early Warning, Guangzhou, ChinaCorrespondence[email protected]
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Yu Zhangb Guangzhou Urban Planning & Design Survey Research Institute, Guangzhou, China;c Collaborative Innovation Center for Natural Resources Planning and Marine Technology of Guangzhou, Guangzhou, China;d Guangdong Enterprise Key Laboratory for Urban Sensing, Monitoring and Early Warning, Guangzhou, ChinaView further author information

Incorporating convolutional and transformer architectures to enhance semantic segmentation of fine-resolution urban images

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Incorporating convolutional and transformer architectures to enhance semantic segmentation of fine-resolution urban images

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