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(8 versions intermédiaires par le même utilisateur non affichées) | |||
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=== When === | === When === | ||
<p>Thursday November 7th, 2019</p> | <p>Thursday November 7th, 2019</p> | ||
− | <p>9:00am - | + | <p>9:00am - 16:00pm</p> |
===Where === | ===Where === | ||
Ligne 9 : | Ligne 9 : | ||
=== Registration === | === Registration === | ||
− | <p>If you want to attend the workshop, please register here | + | <p>If you want to attend the workshop, please register [https://evento.renater.fr/survey/dsai-workshop-novemb...-bw7us7tv here] by '''November 5'''</p> |
− | === | + | === Program === |
{| class="wikitable" | {| class="wikitable" | ||
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| <i>Short presentation</i> ||Baptiste Lafabregue || SDC || A comparison of unsupervised representation learning methods for time series | | <i>Short presentation</i> ||Baptiste Lafabregue || SDC || A comparison of unsupervised representation learning methods for time series | ||
|- | |- | ||
− | !colspan="3"| 15:30 - Closing and coffee break | + | | <i>Short presentation</i> ||Claudine Mayer || CSTB || Deep learning for protein fold recognition |
+ | |- | ||
+ | !colspan="3"| 15:30 - Closing and coffee break - 16:00 | ||
|} | |} | ||
+ | |||
+ | === Format === | ||
+ | - The workshop will be held in English | ||
+ | - Long presentation are 20mn (15mn talk + 5mn questions) | ||
+ | - Short presentation are 10mn (5-7mn talk + 5-3mn questions) | ||
+ | - Meet & Match are 5mn (5mn talk before the coffee break to allow for discussions with potential collaborators) |
Version actuelle datée du 4 novembre 2019 à 20:15
When
Thursday November 7th, 2019
9:00am - 16:00pm
Where
ICube Laboratory, 300 Bd Sébastien Brant, 67400 Illkirch-Graffenstaden - Room A207
Registration
If you want to attend the workshop, please register here by November 5
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 | |||
Long presentation | Emmanuelle Claeys | SDC | Reinforcement learning with time series |
Long presentation | Anne Jeannin-Girardon | CSTB | Transfer Learning: review and recent advances |
Short presentation | Bertrand Goldman | ISU | Stellar streams in the Gaia mission area |
Short presentation | Chinedu Nwoye | AVR | Weakly-supervised convolutional LSTM approach for surgical tool tracking in laparoscopic videos. |
Short presentation | Xin Ni | CSIP | An approach merging the IDM-related knowledge |
Short presentation | Michal Parusinski | SERTIT | AI at SERTIT for remote sensing |
12:20 - Lunch - 14:00 | |||
Long presentation | Argheesh Bhanot | IMAGeS | Online dictionary learning for single-subject fMRI data unmixing |
Long presentation | 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 |
Short presentation | Hyewon Seo | Generating 3D Facial Expressions with RNN | |
Short presentation | Simon Chatelin | AVR | Machine learning for elasticity imaging in biological soft tissue |
Short presentation | Stella Marc-Zwecker | SDC | Spatio-temporal data modeling using graphs |
Short presentation | Thomas Weber | CSTB | RADMEL: An ensemble predictor to reveal disease-relevant missense variants with low degree of uncertainty |
Short presentation | Baptiste Lafabregue | SDC | A comparison of unsupervised representation learning methods for time series |
Short presentation | Claudine Mayer | CSTB | Deep learning for protein fold recognition |
15:30 - Closing and coffee break - 16:00 |
Format
- The workshop will be held in English - Long presentation are 20mn (15mn talk + 5mn questions) - Short presentation are 10mn (5-7mn talk + 5-3mn questions) - Meet & Match are 5mn (5mn talk before the coffee break to allow for discussions with potential collaborators)