6 papers
Overhead Wildlife Locator (OWL): Benchmarking Weakly Supervised Learning for Aerial Wildlife Surveys
Isai Daniel Chacón, Zhongqi Miao, Bruno Demuro +9
Automated aerial wildlife surveys increasingly rely on deep learning, yet standard object detectors require bounding-box annotations, reported to be up to seven times slower and th…
Project SPARROW and the Future of Conservation Technology
Juan M. Lavista Ferres, Carl Chalmers, Bruno Demuro Segundo +14
Global biodiversity is declining at unprecedented rates, yet the tools available to monitor and protect ecosystems remain limited by constraints in power, connectivity, and accessi…
The first global agricultural field boundary map at 10m resolution
Caleb Robinson, Gedeon Muhawenayo, Subash Khanal +9
The agricultural field is the natural unit at which crops are planted, managed, regulated, and reported, yet most global remote-sensing products for agriculture are only available…
WATCH: Wide-Area Archaeological Site Tracking for Change Detection
Girmaw Abebe Tadesse, Titien Bartette, Andrew Hassanali +7
Monitoring archaeological sites at scale is vital for protecting cultural heritage, yet pinpointing when disturbances occur remains difficult because visual cues are subtle and gro…
From Pixels to Patches: Pooling Strategies for Earth Embeddings
Isaac Corley, Caleb Robinson, Inbal Becker-Reshef +1
Geospatial foundation models increasingly expose pixel-level embedding products that can be downloaded and reused without access to the underlying encoder. In this setting, downstr…
BYOL: Bring Your Own Language Into LLMs
Syed Waqas Zamir, Wassim Hamidouche, Boulbaba Ben Amor +3
Large Language Models (LLMs) exhibit strong multilingual capabilities, yet remain fundamentally constrained by the severe imbalance in global language resources. While over 7,000 l…