Human4d
Human4d
Difference between revisions of "ICube KAIST Workshop2023"
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|10h25-11h00||Dr. Minsu Jeon||KAIST, Korea||'''Channel Pruning Optimization for Onboard DL Acceleration''' | |10h25-11h00||Dr. Minsu Jeon||KAIST, Korea||'''Channel Pruning Optimization for Onboard DL Acceleration''' | ||
|- | |- | ||
− | |11h00-11h30||Dr. Hugo Thalbo||SOFA Consortium - ICube laboratory|| '''Coupling Physics | + | |11h00-11h30||Dr. Hugo Thalbo||SOFA Consortium - ICube laboratory|| '''Coupling Physics-Based Simulation and AI''' |
|- | |- | ||
|11h30-14h00||All|| || '''Lunch''' | |11h30-14h00||All|| || '''Lunch''' |
Revision as of 15:58, 12 May 2023
ICube-KAIST Workshop on AI (1st june 2023, Strasbourg)
- Location: Salle IASO, IHU building (1 Pl. de l'Hôpital, 67000 Strasbourg, https://www.ihu-strasbourg.eu/)
Time | Speaker | Affiliation | Title & short abstract |
---|---|---|---|
9h00-9h15 | Hyewon Seo | ICube laboratory - Université de Strasbourg | Welcome & round table
|
9h15-9h50 | Jinhyeok Jang | ETRI & KAIST | Learning to Boost Training by Periodic Nowcasting Near Future Weights |
9h50-10h25 | Kaifeng Zou | ICube laboratory - Université de Strasbourg | 4D Face Diffusion Model |
10h25-11h00 | Dr. Minsu Jeon | KAIST, Korea | Channel Pruning Optimization for Onboard DL Acceleration |
11h00-11h30 | Dr. Hugo Thalbo | SOFA Consortium - ICube laboratory | Coupling Physics-Based Simulation and AI |
11h30-14h00 | All | Lunch | |
14h00-14h35 | Dr. Taewoo Kim | KAIST, Korea | Improving Visual Explainability for Target Recognition in Satellite Imagery Analysis |
14h35-15h10 | Dr. Hyewon Seo | ICube laboratory - Université de Strasbourg | Estimation of LBD and AD’s Severity from Gait Videos Based on 3D Human Motion Reconstruction |
15h10-15h30 | All | Coffee Break | |
15h30-16h05 | Dr. Thomas Lampert | ICube laboratory - Université de Strasbourg | Learning domain invariant representations of heterogeneous remote sensing image data |
16h05-16h40 | Prof. Pierre Collet | ICube laboratory - Université de Strasbourg | Philosophical Exploration on Machine Learning |