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Information Extraction from Very High Resolution Satellite Imagery at Scale: GRSS Live Lecture

Information Extraction from Very High Resolution Satellite Imagery at Scale: GRSS Live Lecture
 15 June, 11am EDT (3pm GMT/UTC)

This live lecture is over and will soon be available in the GRSS Lecture Series Collection. Please stay tuned for information about the next GRSS live lecture.

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As part of a series of live lectures for the IEEE Geoscience & Remote Sensing Society (GRSS), IEEE.tv will broadcast a presentation by Nikki Aldeborgh: "Information Extraction from Very High Resolution Satellite Imagery at Scale."   

ABSTRACT:
This webinar will cover techniques that we've developed at DigitalGlobe to extract information from very high resolution satellite imagery using deep learning. I will discuss feature classification for diverse use cases such as settlement detection and property attribution, as well as semantic segmentation for the delineation of man-made features such as buildings. I will also describe the important challenges that are associated with building and deploying deep learning algorithms at the scale required by satellite imagery analytics applications, and the potential ways forward that we've identified.       

BIOGRAPHY:
Nikki Aldeborgh is a data scientist on the Analytics and Applied Artificial Intelligence team at DigitalGlobe, where she develops algorithms to extract information from DigitalGlobe imagery, as well as the infrastructure for deploying these algorithms at scale on GBDX. She holds a Bachelor's degree in Biochemistry from Vassar College, after which she worked on medical image processing at Memorial Sloan Kettering Cancer Center for several years. She has since honed her machine learning skills at an intensive data science course, which led her to her current position at DigitalGlobe.