Masters Thesis Defense “Fully Transparent Computer Vision Framework for Ship Detection and Tracking in Satellite Imagery” By Jason Gottweis

Thursday, December 13, 10 am to Noon
Campus: 
Dayton
278 Joshi - Visualization Lab
Audience: 
Current Students
Faculty

Committee:  Drs. Thomas Wischgoll, Advisor, Michael Raymer, and John Gallagher

ABSTRACT:

 Tracking of ships in satellite imagery is a challenging problem in remote sensing since it requires both object detection and object recognition. Most of the resources available only cover one of these problems and are often filled with machine learning techniques which are costly to train. Additionally, the techniques covered in these resources are often difficult to replicate or may be hard to combine with other solutions to get a full tracking algorithm.  The proposed framework offers a transparent and efficient alternative to machine learning approaches and includes preprocessing, detection, and recognition needed for tracking. All components of the framework were created based on open source libraries to provide a transparent solution which can be easily modified for specific use cases.

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