Laser & Optoelectronics Progress, Volume. 61, Issue 12, 1228002(2024)
Semantic Segmentation of Remote Sensing Imagery Based on Improved Squeeze and Excitaion Block
[11] Vaswani A, Shazeer N, Parmar N et al. Attention is all You need[C], 6000-6010(2017).
[16] Liu W X, Shu Y Z, Tang X M et al. Remote sensing image segmentation using dual attention mechanism DeepLabV3+ algorithm[J]. Tropical Geography, 40, 303-313(2020).
[17] Fu J, Liu J, Tian H J et al. Dual attention network for scene segmentation[C], 3141-3149(2020).
[24] Jin S, Guan M, Bian Y C et al. Building extraction from remote sensing images based on improved U-Net[J]. Laser & Optoelectronics Progress, 60, 0401002(2023).
[26] Su Z P, Li J W, Jiang J W et al. Semantic segmentation method for remote sensing images based on improved DeepLabV3+[J]. Laser & Optoelectronics Progress, 60, 0628003(2023).
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Shengwei Wu, Jiaoli Fang, Daming Zhu. Semantic Segmentation of Remote Sensing Imagery Based on Improved Squeeze and Excitaion Block[J]. Laser & Optoelectronics Progress, 2024, 61(12): 1228002
Category: Remote Sensing and Sensors
Received: Jun. 13, 2023
Accepted: Aug. 10, 2023
Published Online: May. 20, 2024
The Author Email: Jiaoli Fang (fangjiaoli@163.com)
CSTR:32186.14.LOP231528