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20192026
most citedU.S. Broadband Coverage Data Set: A Differentially Private Data Release

5 citations · 20 across the 24 of their papers we have counts for

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17 papers · 1 filter

cs.CV2026

The Living Library: Transforming Archival Collections into Conversational Knowledge Systems -- Lessons from the Theodore Roosevelt Presidential Library

Pengce Wang, Lucia Ronchi Darre, Matt Briney +8

We present the Living Library, an end-to-end framework for transforming fragmented digital archives into governed, conversational, in-person exhibit experiences. Developed and depl…

cs.CV2026

GeoAI Agency Primitives

Akram Zaytar, Rohan Sawahn, Caleb Robinson +5

We present ongoing research on agency primitives for GeoAI assistants -- core capabilities that connect Foundation models to the artifact-centric, human-in-the-loop workflows where…

cs.CV2025

TEMPO: Global Temporal Building Density and Height Estimation from Satellite Imagery

Tammy Glazer, Gilles Q. Hacheme, Akram Zaytar +9

We present TEMPO, a global, temporally resolved dataset of building density and height derived from high-resolution satellite imagery using deep learning models. We pair building f…

cs.CV2025

Where are the Whales: A Human-in-the-loop Detection Method for Identifying Whales in High-resolution Satellite Imagery

Caleb Robinson, Kimberly T. Goetz, Christin B. Khan +4

Effective monitoring of whale populations is critical for conservation, but traditional survey methods are expensive and difficult to scale. While prior work has shown that whales…

cs.CV2025

Optimizing Cloud-to-GPU Throughput for Deep Learning With Earth Observation Data

Akram Zaytar, Caleb Robinson, Girmaw Abebe Tadesse +5

Training deep learning models on petabyte-scale Earth observation (EO) data requires separating compute resources from data storage. However, standard PyTorch data loaders cannot k…

cs.CV2025

GeoVision Labeler: Zero-Shot Geospatial Classification with Vision and Language Models

Gilles Quentin Hacheme, Girmaw Abebe Tadesse, Caleb Robinson +3

Classifying geospatial imagery remains a major bottleneck for applications such as disaster response and land-use monitoring-particularly in regions where annotated data is scarce…