
Machine Learning on Geospatial Data with Malte Loller-Anderson & Mathilde Ørstavik
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Machine Learning for Urban Structure Recognition
This chapter explores the training of machine learning models to recognize buildings and structures using vector maps and aerial imagery. It discusses the importance of high-quality training data, the sensitivity of models to structural changes like solar panel installations, and the implications for municipal data accuracy and tax assessments. Additionally, it touches on the technical challenges and benefits of using Python and GPU capabilities for handling extensive datasets.
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