News of Heidelberg University’s GIScience Research Group.
Posted in Publications, VGI Group on Mar 11th, 2020
We are pleased to share that because of the response to our work, ISPRS IJGI selected our paper on Detecting Graffiti with Street View Images and Deep Learning to be highlighted as a title story through some graphics on the journals main page.
Novack T, Vorbeck L, Lorei H, Zipf A. (2020): Towards Detecting Building Facades with [...]
Posted in OSM, Publications, Research, VGI Group on Feb 5th, 2020
As a recognized type of art, graffiti is a cultural asset and an important aspect of a city’s aesthetics. As such, graffiti is associated with social and commercial vibrancy and is known to attract tourists. However, positional uncertainty and incompleteness are current issues of open geo-datasets containing graffiti data. In a newly published paper, we [...]
Posted in 3D, Lidar Group, Publications, Research on Oct 2nd, 2019
In a new publication, we show how deep neural networks can be used in an end-to-end manner for the classification of 3D point clouds from airborne laser scan data. The research, based on the award-winning diploma thesis of Lukas Winiwarter at TU Wien, has now been published in “PFG - Photogrammetrie, Fernerkundung, Geoinformation“, the Journal [...]
Posted in Events, Publications, VGI Group on Jun 26th, 2019
Recently a new paper about Estimating OpenStreetMap Missing Built-up Areas using Pre-trained Deep Neural Networks (DNNs) has been presented at the AGILE GIScience conference 2019 in Cyprus.
Although built-up areas cover only a small proportion of the earth’s surface, these areas are closely tied to most of the world’s population and the economic output, which makes the [...]
Posted in Publications on Oct 12th, 2018
Our paper about Deep Learning from Multiple Crowds: A Case Study of Humanitarian Mapping is available online now.
Satellite images are widely applied in humanitarian mapping which labels buildings, roads and so on for humanitarian aid and economic development. However, the labeling now is mostly done by volunteers. In a recently accepted study, we utilize deep learning [...]
Posted in Publications on Aug 16th, 2018
Satellite images are widely applied in humanitarian mapping which labels buildings, roads and so on for humanitarian aid and economic development. However, the labeling now is mostly done by volunteers. In a recently accepted study, we utilize deep learning to solve humanitarian mapping tasks of a mobile software named MapSwipe. The current deep learning techniques [...]
Posted in Events, Lidar Group, Research on Jun 15th, 2018
We cordially invite everybody interested to our next open GIScience colloquium talk
The speaker is Lukas Winiwarter
TU Wien, Department of Geodesy and Geoinformation, Research Group Photogrammetry
When: Monday 18.06.2018, 2:15 pm
Where: INF 348, room 015 (Institute of Geography, Heidelberg University)
Classification of 3D Point Clouds using Deep Neural Networks
Per-point classification (semantic labeling) is an important step in processing topographic 3D [...]