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[1]
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A multi-glimpse deep learning architecture to estimate socioeconomic census metrics in the context of extreme scope variance
International Journal of Geographical Information Science,
2024
DOI:10.1080/13658816.2024.2305636
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[2]
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Harnessing Satellite Imagery with Convolutional Neural Networks for Poverty Prediction
2024 International Conference on Artificial Intelligence and Quantum Computation-Based Sensor Application (ICAIQSA),
2024
DOI:10.1109/ICAIQSA64000.2024.10882295
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[3]
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Spatially granular poverty index (SGPI) for urban poverty mapping in Jakarta metropolitan area (JMA): a remote sensing satellite imageries and geospatial big data approach
Earth Science Informatics,
2023
DOI:10.1007/s12145-023-01084-7
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[4]
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Progress of nighttime light applications within the google earth engine cloud platform
Geocarto International,
2023
DOI:10.1080/10106049.2022.2120550
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[5]
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Methods, data sources and applications of the Artificial Intelligence in the Energy Poverty context: A review
Energy and Buildings,
2022
DOI:10.1016/j.enbuild.2022.112233
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[6]
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Methods, data sources and applications of the Artificial Intelligence in the Energy Poverty context: A review
Energy and Buildings,
2022
DOI:10.1016/j.enbuild.2022.112233
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[7]
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A review of explainable AI in the satellite data, deep machine learning, and human poverty domain
Patterns,
2022
DOI:10.1016/j.patter.2022.100600
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[8]
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Methods, data sources and applications of the Artificial Intelligence in the Energy Poverty context: A review
Energy and Buildings,
2022
DOI:10.1016/j.enbuild.2022.112233
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[9]
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Progress of nighttime light applications within the google earth engine cloud platform
Geocarto International,
2022
DOI:10.1080/10106049.2022.2120550
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[10]
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A review of explainable AI in the satellite data, deep machine learning, and human poverty domain
Patterns,
2022
DOI:10.1016/j.patter.2022.100600
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[11]
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A review of explainable AI in the satellite data, deep machine learning, and human poverty domain
Patterns,
2022
DOI:10.1016/j.patter.2022.100600
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[12]
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Methods, data sources and applications of the Artificial Intelligence in the Energy Poverty context: A review
Energy and Buildings,
2022
DOI:10.1016/j.enbuild.2022.112233
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[13]
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Using Convolutional Neural Networks on Satellite Images to Predict Poverty
2021 12th International Conference on Information and Communication Systems (ICICS),
2021
DOI:10.1109/ICICS52457.2021.9464598
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