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Remote Sensing
ServiceNow Research
Remote Sensing
A General-Purpose Neural Architecture for Geospatial Systems
Geospatial Information Systems are used by researchers and Humanitarian Assistance and Disaster Response (HADR) practitioners to …
Alexandre Lacoste
,
Martin Weiss
,
Nasim Rahaman
Workshop at the Neural Information Processing Systems (NeurIPS), 2022.
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RaVAEn: Unsupervised Change Detection of Extreme Events Using ML On-Board Satellites
Applications such as disaster management enormously benefit from rapid availability of satellite observations. Traditionally, data …
Vít Růžička
,
Anna Vaughan
,
Daniele De Martini
,
James Fulton
,
Valentina Salvatelli
,
Chris Bridges
,
Gonzalo Mateo-Garcia
,
Valentina Zantedeschi
Nature Scientific Reports, 2022.
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Toward Foundation Models for Earth Monitoring: Proposal for a Climate Change Benchmark
Recent progress in self-supervision shows that pre-training large neural networks on vast amounts of unsupervised data can lead to …
Alexandre Lacoste
,
Hannah Kerner
,
Hamed Alemohammad
,
Björn Lütjens
,
Jeremy Irvin
,
David Dao
,
Alex Chang
,
Mehmet Gunturkun
,
Alexandre Drouin
,
Pau Rodriguez
,
David Vazquez
,
Evan D. Sherwin
Workshop at the Neural Information Processing Systems (NeurIPS), 2021.
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Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data
Remote sensing and automatic earth monitoring are key to solve global-scale challenges such as disaster prevention, land use …
Oscar Manas
,
Alexandre Lacoste
,
Xavier Giro-i-Nieto
,
David Vazquez
,
Pau Rodriguez
International Conference on Computer Vision (ICCV), 2021.
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Counting Cows: Tracking Illegal Cattle Ranching From High-Resolution Satellite Imagery
Cattle farming is responsible for 8.8% of greenhouse gas emissions worldwide. In addition to the methane emitted due to their digestive …
Issam H. Laradji
,
Pau Rodriguez
,
Alfredo Kalaitzis
,
David Vazquez
,
Ross Young
,
Ed Davey
,
Alexandre Lacoste
Workshop at the Neural Information Processing Systems (NeurIPS), 2020.
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Extending the Spatial Scale of Land Use Regression Models for Ambient Ultrafine Particles using Satellite Images and Deep Convolutional Neural Networks
We paired existing land use regression (LUR) models for ambient ultrafine particles in Montreal and Toronto, Canada with satellite …
Kris Y. Hong
,
Pedro O. Pinheiro
,
Laura Minet
,
Marianne Hatzopoulou
,
Scott Weichenthal
Journal of Environmental Science, 2019.
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Learning Global Variations in Outdoor PM_2.5 Concentrations with Satellite Images
Here we present a new method of estimating global variations in outdoor PM2.5 concentrations using satellite images combined with …
Yukai (Kris) Hong
,
Pedro O. Pinheiro
,
Scott Weichenthal
Workshop at the International Conference on Machine Learning (ICML), 2019.
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