Marshall Burke

发表

Poverty Prediction with Public Landsat 7 Satellite Imagery and Machine Learning pdf

Stefano Ermon, David B. Lobell, George Azzari, 2017, ArXiv.

Learning to Interpret Satellite Images Using Wikipedia

Stefano Ermon, Chenlin Meng, Evan Sheehan, 2018, IJCAI.

Learning to Interpret Satellite Images in Global Scale Using Wikipedia pdf

Stefano Ermon, Chenlin Meng, Evan Sheehan, 2019, ArXiv.

NBER WORKING PAPER SERIES USING SATELLITE IMAGERY TO UNDERSTAND AND PROMOTE SUSTAINABLE DEVELOPMENT pdf

Anne Driscoll, Stefano Ermon, Marshall Burke, 2020 .

Predicting Livelihood Indicators from Crowdsourced Street Level Images pdf

Stefano Ermon, David B. Lobell, Sicheng Zeng, 2020, ArXiv.

Predicting Economic Development using Geolocated Wikipedia Articles

Stefano Ermon, Chenlin Meng, Evan Sheehan, 2019, KDD.

Infrastructure Quality Assessment in Africa using Satellite Imagery and Deep Learning

Xiao Chen, Stefano Ermon, David B. Lobell, 2018, KDD.

Mapping Missing Population in Rural India: A Deep Learning Approach with Satellite Imagery

Stefano Ermon, Wenjie Hu, Zhongyi Tang, 2019, AIES.

Semantic Segmentation of Crop Type in Africa: A Novel Dataset and Analysis of Deep Learning Methods

Stefano Ermon, Lijing Wang, Marshall Burke, 2019, CVPR Workshops.

Semi-Supervised Multitask Learning on Multispectral Satellite Images Using Wasserstein Generative Adversarial Networks (GANs) for Predicting Poverty pdf

Stefano Ermon, David B. Lobell, Swetava Ganguli, 2019, ArXiv.

Mapping Smallholder Yield Heterogeneity at Multiple Scales in Eastern Africa

David B. Lobell, George Azzari, Marshall Burke, 2017, Remote. Sens..

Transfer Learning from Deep Features for Remote Sensing and Poverty Mapping

Stefano Ermon, David B. Lobell, Sang Michael Xie, 2015, AAAI.

Sight for Sorghums: Comparisons of Satellite- and Ground-Based Sorghum Yield Estimates in Mali

David B. Lobell, Stefania Di Tommaso, Marshall Burke, 2019, Remote. Sens..

Farm Parcel Delineation Using Spatio-temporal Convolutional Networks

Stefano Ermon, Marshall Burke, Burak Uzkent, 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

Generating Interpretable Poverty Maps using Object Detection in Satellite Images

Stefano Ermon, David B. Lobell, Marshall Burke, 2020, IJCAI.

Using publicly available satellite imagery and deep learning to understand economic well-being in Africa

Anne Driscoll, Stefano Ermon, Marshall Burke, 2020, Nature Communications.

Generating Interpretable Poverty Maps using Object Detection in Satellite Images pdf

Stefano Ermon, Marshall Burke, Burak Uzkent, 2020, ArXiv.

Scalable deep learning to identify brick kilns and aid regulatory capacity

Stefano Ermon, David B. Lobell, Stephen P. Luby, 2021, Proceedings of the National Academy of Sciences.

Using Satellite Imagery and Machine Learning to Estimate the Livelihood Impact of Electricity Access

Matthieu Stigler, Marshall Burke, Brandon de la Cuesta, 2021, ArXiv.

Spatial-Temporal Super-Resolution of Satellite Imagery via Conditional Pixel Synthesis pdf

Stefano Ermon, David B. Lobell, Chenlin Meng, 2021, ArXiv.

Twice Is Nice: The Benefits of Two Ground Measures for Evaluating the Accuracy of Satellite-Based Sustainability Estimates

David B. Lobell, Stefania Di Tommaso, Marshall Burke, 2021, Remote. Sens..

Wildfire smoke plume segmentation using geostationary satellite imagery pdf

Marshall Burke, Jeff Wen, M. Burke, 2021, ArXiv.

IS-COUNT: Large-scale Object Counting from Satellite Images with Covariate-based Importance Sampling pdf

Stefano Ermon, Willie Neiswanger, Chenlin Meng, 2021, AAAI.

Efficient Poverty Mapping from High Resolution Remote Sensing Images

Stefano Ermon, David B. Lobell, Marshall Burke, 2021, AAAI.

Predicting Livelihood Indicators from Community-Generated Street-Level Imagery

Stefano Ermon, David B. Lobell, Marshall Burke, 2021, AAAI.

Deep Learning For Crop Yield Prediction in Africa

Stefano Ermon, Marshall Burke, David Lobell, 2019 .

Eyes in the Sky, Boots on the Ground: Assessing Satellite‐ and Ground‐Based Approaches to Crop Yield Measurement and Analysis

Siobhan Murray, George Azzari, Sydney Gourlay, 2018, American Journal of Agricultural Economics.

IPCC WGII AR5 Chapter 22. Africa

David B. Lobell, Marshall Burke, Carla Roncoli, 2014 .

Robust relationship between air quality and infant mortality in Africa

Jennifer Burney, Marshall Burke, Eran Bendavid, 2018, Nature.

International Trade in Meat: The Tip of the Pork Chop

Vaclav Smil, Harold A. Mooney, James N. Galloway, 2007, Ambio.

Incorporating Climate Uncertainty into Estimates of Climate Change Impacts

David B. Lobell, Edward Miguel, Marshall Burke, 2015, Review of Economics and Statistics.

Climate, conflict, and social stability: what does the evidence say?

Marshall Burke, Solomon M. Hsiang, M. Burke, 2013, Climatic Change.

Climate change and food security : adapting agriculture to a warmer world

David B. Lobell, Marshall Burke, D. Lobell, 2010 .

Why are agricultural impacts of climate change so uncertain? The importance of temperature relative to precipitation

David B. Lobell, Marshall Burke, D. Lobell, 2008, Environmental Research Letters.

Eyes in the Sky, Boots on the Ground: Assessing Satellite- and Ground-Based Approaches to Crop Yield Measurement and Analysis in Uganda

Siobhan Murray, George Azzari, Sydney Gourlay, 2018 .

Shifts in African crop climates by 2050, and the implications for crop improvement and genetic resources conservation

David B. Lobell, Luigi Guarino, Marshall Burke, 2009 .

Geography-Aware Self-Supervised Learning pdf

Stefano Ermon, Chenlin Meng, Marshall Burke, 2020, ArXiv.

Smallholder maize area and yield mapping at national scales with Google Earth Engine

David B. Lobell, Stefania Di Tommaso, George Azzari, 2019, Remote Sensing of Environment.

Selling low and buying high: An arbitrage puzzle in Kenyan villages

Marshall Burke, M. Burke, 2014 .