Last week I published this article on Amnesty International's blog, co-authored with Amnesty's human rights researchers.
This is an example of AI helping to protect Human Rights. We discuss new results on satellite imagery of the highest resolution available commercially (Maxar) to help Amnesty track the extent of the Darfur genocide.
A lot of this work is credited to Julien Cornebise, Daniel Worrall, Micah Farfur, Milena Marin who started Decode-Darfur-1 (DD1) in 2017. (see paper published in NeurIPS 2018 AI for Social Good Workshop: https://aiforsocialgood.github.io/2018/pdfs/track1/80_aisg_n...). To Laure Delisle, ZL, Alex Kuefler who continued the project (DD2) in 2019. Buffy Price and I helped bring DD2 to the finish line.
We have no code yet publicly available, not a dataset to reproduce this study - main reasons being that training Maxar imagery come with permission for publicity only. That said, the backbone approach is based on a ResNet50 (pre-trained on ImageNet), so data licensing is the main blocker.
This is an example of AI helping to protect Human Rights. We discuss new results on satellite imagery of the highest resolution available commercially (Maxar) to help Amnesty track the extent of the Darfur genocide.
A lot of this work is credited to Julien Cornebise, Daniel Worrall, Micah Farfur, Milena Marin who started Decode-Darfur-1 (DD1) in 2017. (see paper published in NeurIPS 2018 AI for Social Good Workshop: https://aiforsocialgood.github.io/2018/pdfs/track1/80_aisg_n...). To Laure Delisle, ZL, Alex Kuefler who continued the project (DD2) in 2019. Buffy Price and I helped bring DD2 to the finish line.
We have no code yet publicly available, not a dataset to reproduce this study - main reasons being that training Maxar imagery come with permission for publicity only. That said, the backbone approach is based on a ResNet50 (pre-trained on ImageNet), so data licensing is the main blocker.
Happy to answer any questions.