Predicting per capita expenditure using satellite imagery and transfer learning: A case study of east Java province, Indonesia
Collecting poverty data through the National Socio-Economic Survey (SUSENAS) demands significant time, costs, and human resources. To enable more efficient policy-making, predicting the poverty rate before the release of Statistics Indonesia (BPS) data is essential. This research compares day a...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Growing Science
2025-01-01
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| Series: | International Journal of Data and Network Science |
| Online Access: | https://www.growingscience.com/ijds/Vol9/ijdns_2024_166.pdf |
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