Data Science and Artificial Intelligence Workshop
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
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| Romain Orhand | CSTB | Towards autonomy and explainability in Artificial Intelligence |
| Vinkle Srivastav | AVR | Human Pose Estimation on Privacy-Preserving Low-Resolution Depth Images |
3 Pascal Guehl IGG Creative AI for Texture Synthesis 4 Hugo Gangloff IMAGeS Automatic Segmentation of Atherosclerotic Cross-Sections of Arteries with Deep Learning 5 Yves-Andre Chapuis MaCEPV Accelerated Development of Materials and Devices via Data Analytics and Artificial Intelligence 6 Pei Zhang CSIP Inventive design in AI context 7 Enagnon Aguénounon IPP Fast spatial frequency imaging parameters extraction using generative network 8 Morgan MADEC SMH Optical recognition of bacteria 10:30 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