Speaker Bio & Abstract
BiographyCourtney Layman is a computer vision scientist at Orbital Insight currently focusing on object detection problems. She has built models to track deforestation, detect solar farms across the globe, track crop and water availability in countries at risk of food insecurity, identify land use changes, and detect railcars. She has over 8 years of experience in data science and holds a master''s degree in analytics from Georgia Institute of Technology and bachelor''s degrees in mathematics and computer science from Elon University. AbstractAt Orbital Insight, we have built a platform called GO that combines remote sensing data with machine learning. It allows users to select any location in the world and analyze activity over time using our built-in object detection and geolocation algorithms. The algorithms include foot traffic, land use segmentation, and car, truck, multi-class aircraft, multi-class ship, and railcar detection. Our customers use the platform for many different use cases including defense intelligence, supply chain traceability, real estate development, infrastructure change detection, site and activity monitoring, and economic activity analysis. In this talk, I will discuss how we are using satellite imagery and computer vision at Orbital Insight to extract useful insights and information across many different industries.