SDC, Data Science and Knowledge

Difference between revisions of "Applied research areas"

From SDC, Data Science and Knowledge
Jump to navigation Jump to search
(Created page with "Description")
 
 
(4 intermediate revisions by 2 users not shown)
Line 1: Line 1:
Description
+
 
 +
==Environment and Geography==
 +
 
 +
* Methods for analysis of  remote sensing images all along the process:  image, vectorisation  (objects) , classification
 +
 
 +
===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).
 +
 
 +
==Innovation and Industry==
 +
 
 +
===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.
 +
 
 +
==Health==
 +
 
 +
* Tomographical reconstruction for cryo-electron microscopy

Latest revision as of 18:17, 2 January 2017

Environment and Geography

  • Methods for analysis of remote sensing images all along the process: image, vectorisation (objects) , classification

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).

Innovation and Industry

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.

Health

  • Tomographical reconstruction for cryo-electron microscopy