DEDANet: Mountainous Cropland Extraction From Remote Sensing Imagery With Detail Enhancement and Distance Attenuation
To address the challenge of low automation accuracy in cropland extraction caused by complex mountainous terrain, severe cropland fragmentation, and ambiguous boundaries, this study proposes a novel semantic segmentation model for cropland in high-resolution remote sensing imagery, termed detail-enh...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11072719/ |
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