@article{despotovic_predicting_2017, series = {1}, title = {Predicting {Heating} {Energy} {Demand} by {Computer} {Vision}}, volume = {33}, issn = {1865-2034}, url = {http://www.springer.com/-/1/AV5EQLmWpRR8A1ooSeIw}, doi = {10/gh3772}, abstract = {In many countries such as Austria the heating energy demand (HED) is an essential parameter of the energy certification of houses. In this paper, we present an approach in which the HED category for a single family house is---for the first time---determined from a standard photograph directly by means of computer vision and machine learning.}, journal = {Computer Science - Research and Development}, author = {Despotovic, Miroslav and Sakeena, Muntaha and Koch, David and Döller, Mario and Zeppelzauer, Matthias}, year = {2017}, note = {Projekt: ImmBild Projekt: ImmoAge}, keywords = {2017, Center for Artificial Intelligence, Computer Vision, Department Medien und Digitale Technologien, Department Technologie, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Machine Learning, Media Computing Group, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, Wiss. Beitrag, peer-reviewed}, pages = {231--232}, }