October 2017 – PhD Seminars

Month: October 2017

Networks, Systems and Services, Distributed Computing: Part I

Networks, Systems and Services, Distributed Computing: Part I

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9:00 am: Le Monde des Mathématiques Industrielles (MOMI2019)

9:00 am: Le Monde des Mathématiques Industrielles (MOMI2019)

2:00 pm: PhD Seminars VIII

Upcoming Seminars

Subjects of interest

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Calendar

9:00 am: Le Monde des Mathématiques Industrielles (MOMI2019)

9:00 am: Le Monde des Mathématiques Industrielles (MOMI2019)

2:00 pm: PhD Seminars VIII

Talk 1

Talk 2

Talk 1

Talk 2

Nathalie GAYRAUD 2017/10/09 2017/10/13Seminars 0

Talk 1 Title: How to use Hop and HipHop technologies for the scene: The Massively Interactive Music track. Speaker: Bertrand PETIT and Manuel SERANO – INDES Abstract: In a concert the common way of performing music is largely asymmetric. Most of the time, we have the musicians on one side…

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Upcoming Seminars
- 2:00 pm – 3:00 pm, April 1, 2019 – PhD Seminars IX
Subjects of interest
applied mathematics asteroid exploration biological systems brain combinatorial optimization communication conductivity estimation dynamic dynamics EEG fixed point loops fluid dynamics functional emmbeddings fusion plasmas Galerkin time domain methods git health-biology infection spread invariant manifolds mapping marketing mesh modeling nanophotonics networks networks-systems-distributed-computing neuronal cells numerical simulations optimal transport optimisation optimization pattern recognition PDE protein function radar applications regularization retina routing applications scientific dissemination sed shape matching source localization stochastic gradient algorithm variability workshop
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18 2:00 pm: PhD Seminars VIII March 18, 2019 2:00 pm – 4:00 pm Talk 1 Speaker Nicolas GIRARD (TITANE) Title Aligning and Updating Building Maps with Aerial Images by Multi-Task, Multi-Resolution Deep Learning Abstract A large part of the world is already covered by maps of buildings. However when a new image of an already covered area is captured, it does not align perfectly with the existing map, due to a change of capture conditions, and errors in the map data. Those deformations can only be partially corrected, which leads to misalignments. Leveraging multi-task learning, our model aligns the existing buildings to the new image through a displacement output, and detects new buildings that do not appear in the map through a segmentation output. We also apply our method to buildings height estimation, by aligning to a pair of stereo images. An extension of our work in the noisy-supervision setting allows for the alignement of misaligned building maps without the use of perfect ground truth data for training. Talk 2 Speaker Jean-Philippe BAUCHET (TITANE) Title Kinetic shape approximation Abstract Kinetic data structures consist in a set of geometric primitives whose coordinates are continuous functions of the time. The purpose of such frameworks is to maintain the validity of a set of statements that apply to such primitives over time. In this talk, I will present how kinetic data structures can be used in a context of image partitioning and surface approximation from a point cloud. More