Deep learning has revolutionised image processing and is often considered to outperform classical approaches based on accurate modelling of the image formation process. In this presentation, we will discuss the interplay between model-based and learning-based paradigms, and show that hybrid approaches show great promises for scientific imaging, where interpretation and robustness to real-world degradation is important. We will present two applications on super-resolution and high-dynamic range imaging, and exoplanet detection from direct imaging at high contrast.

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A Coulter counter is an impedance measurement system widely used in blood analyzers to count and size red blood cells, thus providing information about the most numerous cells of the body. In Coulter counters, cells flow through a detection zone where an electric field is imposed, which is disturbed when a cell passes through. The number of these impedance signals yield the red blood cell count, while the cell volume is supposed to be proportional to the amplitude of the signals. However, in real systems, the red blood cells trajectories in the system does not allow to verify the assumptions necessary to provide an accurate volume measurement. For a few years, IMAG has been developing the YALES2BIO solver for the prediction of red blood cell dynamics under flow. In this presentation, I will describe the fluid-structure problem and the numerical method used, then share how numerical simulation has been used to understand the signals in industrial Coulter counters and to improve the measurements of red blood cell volumes rendered by such systems. In addition, I will discuss how the mechanical properties of RBCs impact the measurements. This work has been performed during the PhD theses of Pierre Taraconat and Pierre Pottier (Horiba Medical & IMAG).

Soit $K$ un corps algébriquement clos de caractéristique quelconque. Soit $f \in K[[x,y]]$ une série réduite et $r(f)$ le nombre de ses facteurs irréductibles. Soit $\mathcal{O}=K[[x,y]]/(f)$ et $\overline{\mathcal{O}}$ sa cloture intégrale. On note $\delta(f)=\dim_K \overline{\mathcal{O}}/\mathcal{O}$ et $\mu(f)=\dim_K K[[x,y]]/(f'_x,f'_y)$, le nombre de Milnor. Milnor a montré en 1968 que si $K=\mathbb{C}$,

$$\mu(f)=2\delta(f)-r(f)+1.$$

En 1973, Deligne a montré que si la caractérisque de $K$ est arbitraire

$$\mu(f)\geq 2\delta(f)-r(f)+1.$$

Le but de cet exposé est d'énoncer une conjecture sur la caractéristique de $K$ pour avoir l'égalité.

La conjecture standard de type Hodge porte sur les nombres d'intersections de sous-variétés d'une variété projective. Elle a de nombreuses conséquences en arithmétique, dans cet exposé on construira des variétés abéliennes A qui satisfont à cette conjecture. L'outil principal permettant la construction de variétés abéliennes A est la théorie de Honda-Tate, qui relie ces dernières à des objets de théorie algébrique des nombres. On sera ensuite amené à étudier l'algèbre des classes de Tate de A, qui est un invariant plus manipulable que l'ensemble des sous-variétés de A.