Difference between revisions of "Stella Marc-Zwecker"
Jump to navigation
Jump to search
| Line 15: | Line 15: | ||
* [http://icube-coclico.unistra.fr/ COCLICO] (COllaboration, CLassification, Incrementality and Knowledge) - ANR MN (2012-2016) : my contribution to this project mainly consists in the design of a software platform based on an "image" ontology, which integrates a fuzzy reasoning, that provides a fuzzy classification of image segments into primary classes (vegetation, shadow, water, soil, artificial. This fuzzy classification aims to help the process of segments grouping into urban objects of interest (buildings, roads, parks, etc.). | * [http://icube-coclico.unistra.fr/ COCLICO] (COllaboration, CLassification, Incrementality and Knowledge) - ANR MN (2012-2016) : my contribution to this project mainly consists in the design of a software platform based on an "image" ontology, which integrates a fuzzy reasoning, that provides a fuzzy classification of image segments into primary classes (vegetation, shadow, water, soil, artificial. This fuzzy classification aims to help the process of segments grouping into urban objects of interest (buildings, roads, parks, etc.). | ||
| + | |||
| + | |||
| + | * FOURIRE (Fuzzy Ontologies for URban Image REcognition) - API ICube (2014-2016) : this project, in collaboration with the [http://icube-miv.unistra.fr/ MIV] team, involves the systemic consideration of vagueness and uncertainty in the whole process of urban object recognition. I starts from the level of analysis and interpretation of satellite image (fuzzy segmentation, fuzzy ground truth) until the recognition of image objects (fuzzy qualitative spatial reasoning). | ||
Revision as of 17:25, 4 March 2016
Associate professor at the Computer Science Department of the University of Strasbourg.
Research areas
My research in knowledge representation is mainly applied to the field of semi-automatic recognition of high resolution satellite urban images :
- Domain knowledge modeling using ontologies (semantic web).
- Spatial and temporal qualitative reasoning.
- Modeling vague and imprecise knowledge within ontologies using fuzzy logic.
Research Projects
- COCLICO (COllaboration, CLassification, Incrementality and Knowledge) - ANR MN (2012-2016) : my contribution to this project mainly consists in the design of a software platform based on an "image" ontology, which integrates a fuzzy reasoning, that provides a fuzzy classification of image segments into primary classes (vegetation, shadow, water, soil, artificial. This fuzzy classification aims to help the process of segments grouping into urban objects of interest (buildings, roads, parks, etc.).
- FOURIRE (Fuzzy Ontologies for URban Image REcognition) - API ICube (2014-2016) : this project, in collaboration with the MIV team, involves the systemic consideration of vagueness and uncertainty in the whole process of urban object recognition. I starts from the level of analysis and interpretation of satellite image (fuzzy segmentation, fuzzy ground truth) until the recognition of image objects (fuzzy qualitative spatial reasoning).