#8 Introducing Solaris: CosmiQ’s Open Source Python Library for AI

Performing machine learning and analyzing geospatial data are both hard problems requiring a lot of domain expertise. These limitations have historically meant that one needs to be an expert in both to perform even the most basic analyses, making advances in AI for overhead imagery difficult to achieve. Is there anything we can do to reduce this barrier to entry, making it easier to apply machine learning methods to overhead imagery data?  

Ryan Lewis and Nick Weir tackle that question as they discuss one of CosmiQ’s new project, Solaris, a new open source Python library for performing and evaluating machine learning analyses of overhead imagery. Solaris provides an easy-to-use, end-to-end analysis pipeline for AI model training, prediction, and performance assessment, along with providing pre-trained winning models from the SpaceNet® Chal ...