Addressing spatial imprecision in deep learning for satellite imagery-based socioeconomic predictions
This paper introduces the Spatial Imprecision Adjustment (SIA) method, a neural-network-based post-processing framework designed to enhance the predictive accuracy of geospatial deep learning models trained on imprecise labels, a common challenge in socioeconomic survey data. SIA addresses the chall...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | GIScience & Remote Sensing |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/15481603.2025.2540537 |
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