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18 juin 2018: 1 événement

  • Séminaires Invités

    Lundi 18 juin 14:00-15:30 - Chris Moser - Laboratory of Applied Photonics Devices, Ecole Polytechnique Fédérale de Lausanne, Suisse

    Multimode Optical Fiber Transmission with a Deep Learning Network

    Résumé : Multimode fibers (MMF) are an example of a highly scattering medium which scramble the coherent light propagating within them and produce seemingly random patterns. Thus, for applications such as imaging and image projection through a MMF, careful measurements of the relationship between inputs and outputs of the fiber are required. We will show in the talk that a deep learning neural network can learn the input-output relationship in a 0.75 m long MMF.
    Specifically, we demonstrate that a deep convolutional neural network (CNN) can learn the non-linear relationships between the amplitude of the speckle pattern obtained at the output of the fiber and the phase or amplitude at the input of the fiber. Effectively the network performs a non-linear inversion task. We obtained image fidelity (correlation) of 98% compared with the image obtained using the measured matrix of the system. We further show that the network can be trained for transfer learning, i.e. it can transmit images through the MM fiber which belongs to another class which were not used for training/testing.

    contact : Emmanuel Bossy

    Lieu : LIPhy, conference room - 140 Avenue de la Physique 38402 Saint Martin d’Hères

    En savoir plus : Séminaires Invités