Browsing by Author "Deniz, Oytun"

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    Building Footprint Extraction Using Deep Learning Techniques
    (MEF Üniversitesi, Fen Bilimleri Enstitüsü, 2018) Deniz, Oytun; Gökmen, Muhittin
    Geospatial industry is getting bigger and bigger these days in addition to creating massive amount of data. Today map features such as roads, building footprints are created through manual techniques. There is not automated solution that extracts map features such as roads, building footprints from satellite imagery. Advance automated feature extraction techniques will serve important uses of map data including disaster response. SpaceNet is a commercial satellite imagery and labeled training data to foster innovation in the development of computer vision algorithms. In this paper we will give a brief explanation about image classification, object recognition processes and why deep learning is effective on object recognition, and how we can apply these concepts to our problem which is Building Footprint extraction. And we will use SpaceNet’s dataset and apply tensorflow backhand object detection model.