A cost-effective and robust mapping method for diverse crop types using weakly supervised semantic segmentation with sparse point samples

Cai, Zhiwen; Xu, Baodong; Yu, Qiangyi; Zhang, Xinyu; Yang, Jingya; Wei, Haodong; Li, Shiqi; Song, Qian; Xiong, Hang; Wu, Hao; Wu, Wenbin; Shi, Zhihua; Hu, Qiong

doi:10.1016/j.isprsjprs.2024.09.017

ISPRS Journal of Photogrammetry and Remote Sensing

2024

DOI: 10.1016/j.isprsjprs.2024.09.017

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A cost-effective and robust mapping method for diverse crop types using weakly supervised semantic segmentation with sparse point samples

Zhiwen Cai,

Baodong Xu,

Qiangyi Yu

et al.

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Improving crop type mapping by integrating LSTM with temporal random masking and pixel-set spatial information

Zhang,

Cai,

et al. 2024

ISPRS Journal of Photogrammetry and Remote Sensing

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Improving crop type mapping by integrating LSTM with temporal random masking and pixel-set spatial information

Zhang,

Cai,

et al. 2024

ISPRS Journal of Photogrammetry and Remote Sensing

View full text Add to dashboard Cite

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A cost-effective and robust mapping method for diverse crop types using weakly supervised semantic segmentation with sparse point samples

Cited by 1 publication

References 57 publications

Improving crop type mapping by integrating LSTM with temporal random masking and pixel-set spatial information

Improving crop type mapping by integrating LSTM with temporal random masking and pixel-set spatial information

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