We have a class associated with the lab: CS325b
Sherrie Wang, George Azzari, David Lobell. 2019. “Crop type mapping without field-level labels: Random forest transfer and unsupervised clustering techniques.” Remote Sensing of Environment, 222, 303-317
Neal Jean, Sherrie Wang, Anshul Samar, George Azzari, David Lobell, Stefano Ermon
Tile2Vec: Unsupervised representation learning for spatially distributed data [PDF] AAAI-19. To appear in Proc. 33rd AAAI Conference on Artificial Intelligence, 2019.
Barak Oshri, Annie Hu, Peter Adelson, Xiao Chen, Pascaline Dupas, Jeremy Weinstein, Marshall Burke, David Lobell, Stefano Ermon. 2018. "Infrastructure Quality Assessment in Africa using Satellite Imagery and Deep Learning". Proc. 24th ACM SIGKDD Conference, 2018.
Anthony Perez, Chris Yeh, George Azzari, Marshall Burke, David Lobell, Stefano Ermon. 2017. “Poverty Prediction with Public Landsat 7 Satellite Imagery and Machine Learning”, 31st Conference on Neural Information Processing Systems (NIPS 2017) [PDF]
Jiaxuan You, Xiaocheng Li, Melvin Low, David Lobell, Stefano Ermon
Deep Gaussian Process for Crop Yield Prediction Based on Remote Sensing Data [PDF] [Code] AAAI-17. In Proc. 31st AAAI Conference on Artificial Intelligence, February 2017.
Marshall Burke and David Lobell. 2017. “Satellite-based assessment of yield variation and its determinants in smallholder African systems.” PNAS 114, 9.
Related crop yield work here
Neal Jean, Marshall Burke, MIchael Xie, W. Matt Davis, David Lobell, and Stefano Ermon. 2016. “Combining satellite imagery and machine learning to predict poverty.” Science 353, 6301.
See here for more
Michael Xie, Neal Jean, Marshall Burke, David Lobell, Stefano Ermon
Transfer Learning from Deep Features for Remote Sensing and Poverty Mapping [PDF] [Stanford Report] [NYTimes] AAAI-16. In Proc. 30th AAAI Conference on Artificial Intelligence, February 2016.