Train self-supervised vision transformers on overhead imagery with Amazon SageMaker
AWS Machine Learning
AUGUST 16, 2023
This is a guest blog post co-written with Ben Veasey, Jeremy Anderson, Jordan Knight, and June Li from Travelers. Training machine learning (ML) models to interpret this data, however, is bottlenecked by costly and time-consuming human annotation efforts. Each image is stored in its own folder and contains 12 spectral channels.
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