Difference between revisions of "Applied research areas"
Jump to navigation
Jump to search
| Line 1: | Line 1: | ||
| − | |||
| + | ==Imaging== | ||
| + | * Methods for analysis of remote sensing images all along the process: image, vectorisation (objects) , classification | ||
| + | * Tomographical reconstruction for cryo-electron microscopy | ||
| + | |||
| + | ==Environment and Water== | ||
| + | ===Knowledge extraction from spatio-temporal data in environmental domains=== | ||
Spatio-temporal data are numerous in environmental domains, e.g. agroecology or hydroecology. These domains also require to develop operational tools to help in the interpretation of the complex information concerning their functioning, as well as the results of ongoing action programmes. To exploit these data we adopt a knowledge discovery process. We both work on data structuration and preparation, and propose to explore various data mining approaches and make them collaborating, always involving experts from other labs (LIVE Strasbourg, TETIS Montpellier, INRA Mirecourt). | Spatio-temporal data are numerous in environmental domains, e.g. agroecology or hydroecology. These domains also require to develop operational tools to help in the interpretation of the complex information concerning their functioning, as well as the results of ongoing action programmes. To exploit these data we adopt a knowledge discovery process. We both work on data structuration and preparation, and propose to explore various data mining approaches and make them collaborating, always involving experts from other labs (LIVE Strasbourg, TETIS Montpellier, INRA Mirecourt). | ||
| + | |||
| + | ==Industry 4.0== | ||
| + | * Formalisation of the communication layers in the framework of Smart Factories | ||
| + | * Understanding the tactile perception of a product, with focus on sensory measurements in production. | ||
Revision as of 19:16, 25 February 2016
Imaging
- Methods for analysis of remote sensing images all along the process: image, vectorisation (objects) , classification
- Tomographical reconstruction for cryo-electron microscopy
Environment and Water
Knowledge extraction from spatio-temporal data in environmental domains
Spatio-temporal data are numerous in environmental domains, e.g. agroecology or hydroecology. These domains also require to develop operational tools to help in the interpretation of the complex information concerning their functioning, as well as the results of ongoing action programmes. To exploit these data we adopt a knowledge discovery process. We both work on data structuration and preparation, and propose to explore various data mining approaches and make them collaborating, always involving experts from other labs (LIVE Strasbourg, TETIS Montpellier, INRA Mirecourt).
Industry 4.0
- Formalisation of the communication layers in the framework of Smart Factories
- Understanding the tactile perception of a product, with focus on sensory measurements in production.