Différences entre les versions de « Data Science and Artificial Intelligence Workshop »
| Ligne 18 : | Ligne 18 : | ||
| 09:00 Introduction | | 09:00 Introduction | ||
|- | |- | ||
| − | | Romain Orhand || CSTB || Towards autonomy and explainability in Artificial Intelligence | + | | Long presentation || Romain Orhand || CSTB || Towards autonomy and explainability in Artificial Intelligence |
|- | |- | ||
| − | | Vinkle Srivastav || AVR || Human Pose Estimation on Privacy-Preserving Low-Resolution Depth Images | + | | Long presentation || Vinkle Srivastav || AVR || Human Pose Estimation on Privacy-Preserving Low-Resolution Depth Images |
|- | |- | ||
| − | | Pascal Guehl || IGG || Creative AI for Texture Synthesis | + | | Short presentation || Pascal Guehl || IGG || Creative AI for Texture Synthesis |
|- | |- | ||
| − | | Hugo Gangloff || IMAGeS || Automatic Segmentation of Atherosclerotic Cross-Sections of Arteries with Deep Learning | + | | Short presentation || Hugo Gangloff || IMAGeS || Automatic Segmentation of Atherosclerotic Cross-Sections of Arteries with Deep Learning |
|- | |- | ||
| − | | Yves-Andre Chapuis || MaCEPV || Accelerated Development of Materials and Devices via Data Analytics and Artificial Intelligence | + | | Meet&Match || Yves-Andre Chapuis || MaCEPV || Accelerated Development of Materials and Devices via Data Analytics and Artificial Intelligence |
|- | |- | ||
| − | | Pei Zhang || CSIP || Inventive design in AI context | + | | Meet&Match || Pei Zhang || CSIP || Inventive design in AI context |
|- | |- | ||
| − | | Enagnon Aguénounon || IPP || Fast spatial frequency imaging parameters extraction using generative network | + | | Meet&Match || Enagnon Aguénounon || IPP || Fast spatial frequency imaging parameters extraction using generative network |
|- | |- | ||
| − | | | + | | Meet&Match || Morgan Madec || SMH || Optical recognition of bacteria |
| − | | 10:30 | + | | <b>10:30 Coffee break</b> |
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Version du 30 septembre 2019 à 18:24
ICube Data Science and Artificial Intelligence
When
Thursday November 7th, 2019
9:00am - 15:30pm
Where
ICube Laboratory, 300 Bd Sébastien Brant, 67400 Illkirch-Graffenstaden
(Room A207).
Registration
If you want to attend the workshop, please register here: [link]
Temporary program
| 09:00 Introduction | ||||
| Long presentation | Romain Orhand | CSTB | Towards autonomy and explainability in Artificial Intelligence | |
| Long presentation | Vinkle Srivastav | AVR | Human Pose Estimation on Privacy-Preserving Low-Resolution Depth Images | |
| Short presentation | Pascal Guehl | IGG | Creative AI for Texture Synthesis | |
| Short presentation | Hugo Gangloff | IMAGeS | Automatic Segmentation of Atherosclerotic Cross-Sections of Arteries with Deep Learning | |
| Meet&Match | Yves-Andre Chapuis | MaCEPV | Accelerated Development of Materials and Devices via Data Analytics and Artificial Intelligence | |
| Meet&Match | Pei Zhang | CSIP | Inventive design in AI context | |
| Meet&Match | Enagnon Aguénounon | IPP | Fast spatial frequency imaging parameters extraction using generative network | |
| Meet&Match | Morgan Madec | SMH | Optical recognition of bacteria | 10:30 Coffee break |
11:00 1 Emmanuelle Claeys SDC Reinforcement learning with time series 2 Anne Jeannin-Girardon CSTB Transfer Learning: review and recent advances 3 Bertrand Goldman Other Stellar streams in the Gaia mission area 4 Chinedu Nwoye AVR Weakly-supervised convolutional LSTM approach for surgical tool tracking in laparoscopic videos. 5 Xin Ni CSIP An approach merging the IDM-related knowledge 6 Michal Parusinski Other AI at SERTIT for remote sensing 12:20 Lunch 14:00 1 Argheesh Bhanot IMAGeS Online dictionary learning for single-subject fMRI data unmixing 2 Birgitta Dresp-Langley IGG The quantization error in the Self-Organizing Map (SOM) output as a diagnostic tool for single-pixel change in complex patterns 3 Hyewon Seo Other Generating 3D Facial Expressions with RNN 4 Simon Chatelin AVR Machine learning for elasticity imaging in biological soft tissue 5 Stella MARC-ZWECKER SDC Spatio-temporal data modeling using graphs 6 Thomas Weber CSTB RADMEL: An ensemble predictor to reveal disease-relevant missense variants with low degree of uncertainty 7 Baptiste Lafabregue SDC A comparison of unsupervised representation learning methods for time series