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Robust detection of astronomical sources using convolutional neural networksClosing date: 2017-03-31
Contact: Hervé Bouy
The goal of this thesis is to address the problem of detecting and deblending sources by means of deep convolutional neural networks. In contrast to machine learning techniques that have already been applied to astronomical data, the aim here will be to define and apply a multi-instance pixel labelling method directly from a heterogeneous set of multichannel images, relying on state-of-the-art techniques in the field. The sky background and the high dynamic range that characterize astronomical images will have to be taken into account.
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