Eulalie Boucher

Observatoire de Paris

After studying applied mathematics and deep learning at University Paris-Dauphine, Chalmers University and École Polytechnique, Eulalie Boucher is now pursuing a PhD at LERMA, Observatoire de Paris studying the uses of Deep Learning for infrared spectrometers.

The uses of Deep Learning for remote sensing: results and challenges when using polar orbiting satellites

Using statistical modeling for the inversion of surface or atmospheric properties from satellite observations has been common for the last 20-30 years but only at the pixel level, especially for coarse resolution infrared instruments placed onboard polar orbiting satellites. We present here a first use of Convolutional Neural Networks for the IASI instrument.