Difference between revisions of "Projects"
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* ACE_game (2018-2019) : Anomaly detection by intelligent agents | * ACE_game (2018-2019) : Anomaly detection by intelligent agents | ||
| + | * METEC-Graphe (2019-2020): Modeling of spatial and temporal data for the extraction of knowledge via the use of graphs | ||
==Past projects== | ==Past projects== | ||
Revision as of 16:51, 24 April 2019
Current projects
- HALFBACK (2017-2020) : Highly available smart factories in the cloud. Funded in the framework of the INTERREG V Upper Rhine program, through the Offensive Sciences call for projects of the Tri-National Metropolitan Region of the Upper Rhine. Partners: Hochschule Furtwangen (leading partner), INSA Strasbourg, Université de Strasbourg. Associate Partners: Kirner Schleifmaschinen GmbH & Co. KG. , Senk OHG CNC-Fräs- & Graviertechnik, Industrie Informatik GmbH & Co.KG, inovex GmbH, GTEO, INEVA SAS, Rhénatic.
- DA_HPC_OR (2018-2019) : EUCOR Seed Money - Data Analysis for High Performance Computing : Operation and Research
- SysMIFTA (2016-2019): ERACoSysMed - Systems medicine approach to minimize macrophage-associated interstitial fibrosis and tubular atrophy in renal allograft rejection
- Sysimit (2013-2019): BMBF - Systems Immunology and Image Mining in Translational Tissue Biomarker Research: Mining the spatial patterns of adaptive immune responses to persisting tissue antigens to exploit the full predictive potential of protocol biopsies in transplantation and cancer research
Local projects
- ACE_game (2018-2019) : Anomaly detection by intelligent agents
- METEC-Graphe (2019-2020): Modeling of spatial and temporal data for the extraction of knowledge via the use of graphs
Past projects
- SEMNET (Sensor Networks for Smart Factories) - API ICube (2017-2018): this projet is an internal collaboration with the Network research team. Its objective is to analyze experimental data collected from the IoT-Lab (Internet of Things platform of the Network team), by applying data mining and machine learning techniques, in order to better understand the behaviour of the sensor network, and to propose algorithms for the diagnosis of network failure.
- NEUROTEX - API ICube (2017-2018): this project is an internal collaboration with the IGG research team. Convolutional neural networks for texture synthesis.
- Exploratory analysis of muddy flood representations in Alsace: extracting and formalizing graphical information (2016-2017). ENGEES conseil scientifique.
- FOURIRE (Fuzzy Ontologies for URban Image REcognition) - API ICube (2014-2016): this projet is an internal collaboration with the MIV research team. Its goal is to take into account uncertainty through the whole process of semi-automatic recognition of urban objects from satellite Very High Resolution images.
- Coclico (2012-2016): ANR MN - COllaboration, CLassification, Incrémentalité et COnnaissances
- Reframe project (2012-2016): CHIST-ERA - Rethinking the Essence, Flexibility and Reusability of Advanced Model Exploitation
- DAWSHI (2014-2015): ICube internal project - Deep Analysis of Whole Slide Histopathological Images
- Fresqueau (2011-2015): ANR 11 MONU 14 - "Data mining for assessing and monitoring the hydrobiologic quality of running waters"