Différences entre les versions de « Deep Learning Tutorial 2019 »
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<center><h1><br />'''DSAI DEEP LEARNING TUTORIAL'''<br /><br /></h1></center> | <center><h1><br />'''DSAI DEEP LEARNING TUTORIAL'''<br /><br /></h1></center> | ||
| − | <table style='width:100%; | + | <table style='width:100%;'> |
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<td> Pre-registeration survey </td> | <td> Pre-registeration survey </td> | ||
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<td> Syllables </td> | <td> Syllables </td> | ||
<td> Requirements </td> | <td> Requirements </td> | ||
| − | <td> Installation package </td> | + | <td> [https://icube-forge.unistra.fr/CAMMA/misc/dsai_dl_tutorial Installation package] </td> |
| − | <td> Download dataset </td> | + | <td> [http://camma.u-strasbg.fr/datasets Download dataset] </td> |
| − | <td> Contact us </td> | + | <td> [http://camma.u-strasbg.fr/contact Contact us] </td> |
</tr> | </tr> | ||
</table> | </table> | ||
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| + | <center><div align="center" style="border:2px solid black; background:#fef6e7; color:blue; align:center; width:400px" > Registration deadline: June 20, 2019</div></center> | ||
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| − | <p>DSAI DL 2019 will be a research tutorial event with a global scope aiming at updating participants about the most recent advances in the critical and fast developing area of deep learning. This is a branch of artificial intelligence covering a spectrum of current exciting machine learning research and industrial innovation that provides more efficient algorithms to deal with large-scale data in neurosciences, computer vision, speech recognition, language processing, human-computer interaction, drug discovery, biomedical informatics, healthcare, recommender systems, learning theory, robotics, games, etc. Renowned academics and industry pioneers will lecture and share their views with the audience. < | + | <p>DSAI DL 2019 will be a research tutorial event with a global scope aiming at updating participants about the most recent advances in the critical and fast developing area of deep learning. This is a branch of artificial intelligence covering a spectrum of current exciting machine learning research and industrial innovation that provides more efficient algorithms to deal with large-scale data in neurosciences, computer vision, speech recognition, language processing, human-computer interaction, drug discovery, biomedical informatics, healthcare, recommender systems, learning theory, robotics, games, etc. Renowned academics and industry pioneers will lecture and share their views with the audience. </p><p> DSAI DL 2019 will be a research tutorial event with a global scope aiming at updating participants about the most recent advances in the critical and fast developing area of deep learning. This is a branch of artificial intelligence covering a spectrum of current exciting machine learning research and industrial innovation that provides more efficient algorithms to deal with large-scale data in neurosciences, computer vision, speech recognition, language processing, human-computer interaction, drug discovery, biomedical informatics, healthcare, recommender systems, learning theory, robotics, games, etc. Renowned academics and industry pioneers will lecture and share their views with the audience.[..dummy writing..] </p><p> DSAI DL 2019 will be a research tutorial event with a global scope aiming at updating participants about the most recent advances in the critical and fast developing area of deep learning. This is a branch of artificial intelligence covering a spectrum of current exciting machine learning research and industrial innovation that provides more efficient algorithms to deal with large-scale data in neurosciences, computer vision, speech recognition, language processing, human-computer interaction, drug discovery, biomedical informatics, healthcare, recommender systems, learning theory, robotics, games, etc. Renowned academics and industry pioneers will lecture and share their views with the audience.[..dummy writing..] </p> |
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<td> [[Image:Deeplearn.jpeg|500x300 px|right|link=CAMMA]] </td> | <td> [[Image:Deeplearn.jpeg|500x300 px|right|link=CAMMA]] </td> | ||
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<tr><td colspan="2"><br /><br /><big> <big>'''Date & Venue'''</big> </big></td></tr> | <tr><td colspan="2"><br /><br /><big> <big>'''Date & Venue'''</big> </big></td></tr> | ||
| − | <tr> | + | <tr style="border: 2px solid black; background: #F5F5F5;"> |
<td> [[Image:icube.jpg|500x500 px|left|link=ICube]] </td> | <td> [[Image:icube.jpg|500x500 px|left|link=ICube]] </td> | ||
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<tr><td colspan="2"><br /><br /><big> <big>'''Syllables'''</big> </big></td></tr> | <tr><td colspan="2"><br /><br /><big> <big>'''Syllables'''</big> </big></td></tr> | ||
| − | <tr> | + | <tr style="border: 2px solid black; background: #EEF5F5;"> |
<td> Syllables </td> | <td> Syllables </td> | ||
<td> Contact us </td> | <td> Contact us </td> | ||
| + | </tr> | ||
| + | </table> | ||
| + | |||
| + | <table style='width:100% > | ||
| + | <tr><td colspan="2"><br /><br /><big> <big>'''Speakers'''</big> </big></td></tr> | ||
| + | <tr style="border: 2px solid black; background: #F5F5F5;"> | ||
| + | <td><td> | ||
| + | <td> [[Image:NP.jpg|126 px|center|link=Nicolas Padoy]] <center><b>Nicolas Padoy</b> <br /> <i>Professor<br /> University of Strasbourg. </i></center> </td> | ||
| + | <td><td> | ||
| + | <td> [[Image:Tong.jpg|150 px|center|link=Tong]] <center><b>Tong Yu </b> <br /> <i>PhD Student<br /> University of Strasbourg. </i></center> </td> | ||
| + | <td><td> | ||
| + | <td> [[Image:Chinedu.jpg|150 px|center|link=Chinedu]] <center><b>Chinedu Nwoye </b> <br /> <i>PhD Student<br /> University of Strasbourg. </i></center> </td> | ||
| + | <td><td> | ||
| + | <td> [[Image:Armine.jpg|130 px|center|link=Armine]] <center><b>Armine Vardazaryan </b> <br /> <i>Research Engineer<br /> ICube Laboratory. </i></center> </td> | ||
| + | <td><td> | ||
| + | <td> [[Image:Vinkle.png|130 px|center|link=Vinkle]] <center><b>Vinkle Kumar Srivasta </b> <br /> <i>PhD Student<br /> University of Strasbourg. </i></center> </td> | ||
| + | <td><td> | ||
| + | <td> [[Image:Thomas.jpg|Thomas Lampert|center|link=Thomas]] <center><b> Thomas Lampert </b> <br /> <i>Professor<br /> University of Strasbourg. </i></center> </td> | ||
| + | <td><td> | ||
</tr> | </tr> | ||
</table> | </table> | ||
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| − | == | + | == Participatory Requirements == |
Version du 4 juin 2019 à 16:48
DSAI DEEP LEARNING TUTORIAL
| Pre-registeration survey | Registration | Syllables | Requirements | Installation package | Download dataset | Contact us |
Scope | |
|
DSAI DL 2019 will be a research tutorial event with a global scope aiming at updating participants about the most recent advances in the critical and fast developing area of deep learning. This is a branch of artificial intelligence covering a spectrum of current exciting machine learning research and industrial innovation that provides more efficient algorithms to deal with large-scale data in neurosciences, computer vision, speech recognition, language processing, human-computer interaction, drug discovery, biomedical informatics, healthcare, recommender systems, learning theory, robotics, games, etc. Renowned academics and industry pioneers will lecture and share their views with the audience. DSAI DL 2019 will be a research tutorial event with a global scope aiming at updating participants about the most recent advances in the critical and fast developing area of deep learning. This is a branch of artificial intelligence covering a spectrum of current exciting machine learning research and industrial innovation that provides more efficient algorithms to deal with large-scale data in neurosciences, computer vision, speech recognition, language processing, human-computer interaction, drug discovery, biomedical informatics, healthcare, recommender systems, learning theory, robotics, games, etc. Renowned academics and industry pioneers will lecture and share their views with the audience.[..dummy writing..] DSAI DL 2019 will be a research tutorial event with a global scope aiming at updating participants about the most recent advances in the critical and fast developing area of deep learning. This is a branch of artificial intelligence covering a spectrum of current exciting machine learning research and industrial innovation that provides more efficient algorithms to deal with large-scale data in neurosciences, computer vision, speech recognition, language processing, human-computer interaction, drug discovery, biomedical informatics, healthcare, recommender systems, learning theory, robotics, games, etc. Renowned academics and industry pioneers will lecture and share their views with the audience.[..dummy writing..] |
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Date & Venue | |
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Date & Time: Tuesday, December 11, 2018, 9am-5pm Venue: Forum (Amphitheater 301-302), 4 rue Kirschleger, Faculté de Médecine, Strasbourg |
Syllables | |
| Syllables | Contact us |
Speakers | |||||||||||||||||||
 Professor University of Strasbourg. |
 PhD Student University of Strasbourg. |
 PhD Student University of Strasbourg. |
 Research Engineer ICube Laboratory. |
 PhD Student University of Strasbourg. |
 Professor University of Strasbourg. |
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