dida is involved in two ZIM networks, agraSpace and CopServ and will therefore attend the yearly meeting of ZIM networks in Berlin September 24th. This year's topic "AI for the German Mittelstand -...read more
June 15th, 2018
Philipp Jackmuth © dida
At this year's Predictive Analytics World Industry 4.0 conference, we were asked to present a case study on how we used deep learning in a business application.
We decided to showcase a recently developed software program that is able to predict from image data the number of solar panels which can be fit on a specific house. This application needs to be fed with address data as input and delivers within seconds accurate estimates of the roof area and the number of solar panels. We started out with a live- demonstration of the application and then moved on to explain the inner workings, especially the image segmentation part where we used deep learning. Thanks so much to our customer Enpal for taking the time to co-present the application.
September 23rd, 2019