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Search Results for 'deep learning'

After more than a decade of rapid development of volunteered geographic information (VGI), VGI has already become one of the most important research topics in the GIScience community. Almost in the meantime, we have witnessed the ever-fast growth of geospatial deep learning technologies to develop smart GIServices and to address remote sensing tasks, for instance, [...]

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Am 02.07. besuchte eine Delegation von Alumni von “Jugend präsentiert” im Rahmen der diesjährigen Summer School REMOTE von “Jugend präsentiert” das Heidelberg Institute for Geoinformation Technology (HeiGIT gGmbH) an der Universität Heidelberg. Aufgrund der Corona-Pandemie fand der Besuch allerdings nur virtuell statt: Prof. Alexander Zipf berichtete und diskutierte in einem Online-Meeting mit den Teilnehmerinnen über die [...]

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Multi-sensor remote sensing image classification has been considerably improved by deep learning feature extraction and classification networks. In this recent paper, we propose a novel multi-sensor fusion framework (CResNet-AUX) for the fusion of diverse remote sensing data sources. The novelty of this paper is grounded in three important design innovations:

A unique adaptation of the [...]

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The Humanitarian OpenStreetMap Team (HOT) has announced major financial support from the Audacious Project, which will be provided over the next five years. HOT aims to use this funding to grow OpenStreetMap (OSM) communities in 94 countries. By engaging one million volunteers the goal is to map an area home to one billion people living [...]

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Accurate and detailed geographical information digitizing human activity patterns plays an essential role in response to natural disasters. Volunteered geographical information, in particular OpenStreetMap (OSM), shows great potential in providing the knowledge of human settlements to support humanitarian aid, while often the availability and quality of OSM remains a major concern. The majority of existing [...]

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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 [...]

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This week, at the prestigious GSMA MWC series (formally known as Mobile World Congress) MapSwipe was awarded the top prize in the Global Mobile Awards’ category for the Best Mobile Innovation Supporting Emergency or Humanitarian Situations. The award recognizes how mobile connectivity can provide a lifeline in major humanitarian disasters, providing access to critical information and [...]

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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 [...]

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From 4-5 December 2019, the 2nd International Workshop Point Cloud Processing was co-organized by euroSDR, the German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF) and the Institute for Photogrammetry (ifp) at the University of Stuttgart.
The aim of the workshop was to present and discuss the processing and evaluation of [...]

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Happy Birthday Missing Maps! On the occasion of the recently launched Missing Maps 5 Years Birthday Blog, that also highlighted our latest Missing Maps related HeiGIT and ohsome projects, we put together an overview of our years with and within the Missing Maps.
November 2014 the Missing Maps project was launched by the British and American [...]

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