| Published | Deadline | Location |
|---|---|---|
| yesterday | 4 Dec | Enschede |
Job description
Maps are quickly becoming outdated, about 10 % of the objects change annually. This project focuses on methods to automatically interpret newly acquired sensor data to detect and update the changed objects in the digital map. The sensor data includes high resolution 2D aerial image data and 3D laser scanner data. Our approach is to use the existing (old) digital maps to learn how various objects appear in these 2D and 3D datasets. The PhD researcher’s task is to design a deep learning network to semantically segment airborne sensor data, making use of a huge training dataset derived from the fusion of map and sensor data. For (3D) point clouds derived from stereo (2D) images we aim to build a combined 3D and 2D classification approach, to be able to later classify both point clouds and imagery. Alongside this PhD position, one Postdoc will work on the generation of training data, and one other PhD student will work on the delineation of data into map objects.
The specific tasks in this project are to design of neural networks for image and point cloud classification using massive training data, to image and point cloud classification and domain adaptation, and to change detection between sensor data and map data.
Specifications
University of Twente (UT)
Requirements
Conditions of employment
Department
The Department of Earth Observation Science (EOS) is engaged in education, research and capacity building on earth observation, image analysis and geo-health. The department develops and applies methods for the extraction of large scale geo-information from airborne and terrestrial sensors. It holds expertise in laser scanning technology, sensor integration, point cloud processing, scene understanding and 3D landscape and building modelling. The expertise of the department covers spatial statistics, image analysis, deep learning, monitoring and data integration. Geo-health relates the dynamics of diseases to the geo context. This is done by modelling the spread of diseases and their explanatory variables and includes the understanding of the emergence of diseases at various scales.
Additional information
Additional information about this position can be obtained from Dr Oude Elberink (email: s.j.oudeelberink@utwente.nl) or from Prof Vosselman (email: george.vosselman@utwente.nl). You are also invited to visit our homepage.
Please submit your application before 5 December 2022. Your application should include:
Names and e-mail addresses of three references
The University of Twente wants to be an organisation that optimally deploys diversity, talents and capabilities in the labour market for now and the future. In the framework of our diversity and inclusiveness policy, we strongly stimulate people with a (work) disability to apply for this position.
High Tech and Human Touch
Join the university of technology that puts people first. Create new possibilities for yourself, your colleagues and society as a whole. Using modern technology and science to drive innovation, change and progress. That’s what it means to work at the University of Twente.
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