Complex System Inc.

Published purpose

Earth observation with large spatial coverage, high temporal revisits make an attractive option for continuous monitoring of Earth. The objective is to develop a software framework that leverages AI and processing tools to automatically search and discover events or objects of interest. To focus on overcoming the data limitation problem, with an innovative approach that combines few-shot learning paradigm with synthetic data generation and a use case for rare events, objects, or anomalies. A generative model will also be developed to learn the transformation between different sensor types to generate synthetic satellite images. To address the high dimensionality of satellite image data, we propose a patch/region-based approach to generation.