55 citations · 83 across the 4 of their papers we have counts for
5 papers
Unlocking large-scale crop field delineation in smallholder farming systems with transfer learning and weak supervision
Sherrie Wang, Francois Waldner, David B. Lobell
Crop field boundaries aid in mapping crop types, predicting yields, and delivering field-scale analytics to farmers. Recent years have seen the successful application of deep learn…
SustainBench: Benchmarks for Monitoring the Sustainable Development Goals with Machine Learning
Christopher Yeh, Chenlin Meng, Sherrie Wang +7
Progress toward the United Nations Sustainable Development Goals (SDGs) has been hindered by a lack of data on key environmental and socioeconomic indicators, which historically ha…
Two Shifts for Crop Mapping: Leveraging Aggregate Crop Statistics to Improve Satellite-based Maps in New Regions
Dan M. Kluger, Sherrie Wang, David B. Lobell
Crop type mapping at the field level is critical for a variety of applications in agricultural monitoring, and satellite imagery is becoming an increasingly abundant and useful raw…
Meta-Learning for Few-Shot Land Cover Classification
Marc Rußwurm, Sherrie Wang, Marco Körner +1
The representations of the Earth's surface vary from one geographic region to another. For instance, the appearance of urban areas differs between continents, and seasonality influ…
Tile2Vec: Unsupervised representation learning for spatially distributed data
Neal Jean, Sherrie Wang, Anshul Samar +3
Geospatial analysis lacks methods like the word vector representations and pre-trained networks that significantly boost performance across a wide range of natural language and com…