2 citations · 5 across the 7 of their papers we have counts for
8 papers
Generalizable Slum Detection from Satellite Imagery with Mixture-of-Experts
Sumin Lee, Sungwon Park, Jeasurk Yang +2
Satellite-based slum segmentation holds significant promise in generating global estimates of urban poverty. However, the morphological heterogeneity of informal settlements presen…
EconCausal: A Context-Aware Economic Reasoning Benchmark for Large Language Models
Donggyu Lee, Hyeok Yun, Meeyoung Cha +3
Socio-economic causal effects depend heavily on their institutional and environmental contexts. The same intervention can produce different, even opposite, effects across regulator…
Learning Multidimensional Urban Poverty Representation with Satellite Imagery
Sungwon Park, Sumin Lee, Jihee Kim +4
Recent advances in deep learning have enabled the inference of urban socioeconomic characteristics from satellite imagery. However, models relying solely on urbanization traits oft…
GeoReg: Weight-Constrained Few-Shot Regression for Socio-Economic Estimation using LLM
Kyeongjin Ahn, Sungwon Han, Seungeon Lee +6
Socio-economic indicators like regional GDP, population, and education levels, are crucial to shaping policy decisions and fostering sustainable development. This research introduc…
GeoSEE: Regional Socio-Economic Estimation With a Large Language Model
Sungwon Han, Donghyun Ahn, Seungeon Lee +5
Moving beyond traditional surveys, combining heterogeneous data sources with AI-driven inference models brings new opportunities to measure socio-economic conditions, such as pover…
Generalizable Disaster Damage Assessment via Change Detection with Vision Foundation Model
Kyeongjin Ahn, Sungwon Han, Sungwon Park +3
The increasing frequency and intensity of natural disasters call for rapid and accurate damage assessment. In response, disaster benchmark datasets from high-resolution satellite i…
Fine-Grained Socioeconomic Prediction from Satellite Images with Distributional Adjustment
Donghyun Ahn, Minhyuk Song, Seungeon Lee +5
While measuring socioeconomic indicators is critical for local governments to make informed policy decisions, such measurements are often unavailable at fine-grained levels like mu…
Learning Economic Indicators by Aggregating Multi-Level Geospatial Information
Sungwon Park, Sungwon Han, Donghyun Ahn +8
High-resolution daytime satellite imagery has become a promising source to study economic activities. These images display detailed terrain over large areas and allow zooming into…