Predicting socioeconomic indicators using transfer learning on imagery data: an application in Brazil
Author:
Publisher
Springer Science and Business Media LLC
Subject
Geography, Planning and Development
Link
https://link.springer.com/content/pdf/10.1007/s10708-022-10618-3.pdf
Reference52 articles.
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3. Bai, R., Lam, J. C. K., & Li, V. O. K. (2020). Siamese-like convolutional neural network for fine-grained income estimation of developed economies. IEEE Access, 8, 162533–162547. https://doi.org/10.1109/ACCESS.2020.3019239.
4. Bennett, M. M., & Smith, L. C. (2017). Advances in using multitemporal night-time lights satellite imagery to detect, estimate, and monitor socioeconomic dynamics. Remote Sensing of Environment, 192, 176–197. https://doi.org/10.1016/j.rse.2017.01.005.
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