Hyper-spectral imaging is a powerful technique in geology, physics, astronomy and biomedical imaging. Recently, the volume of of hyper-spectral data has skyrocketed over the past decade. This surge in large volumes of data related to 3D data calls for efficient classification methods in order to explore these large hyper-spectral data-sets without a priori assumptions and classification has become the bottleneck in many areas. In this context, it is thus urgent to develop versatile algorithms to classify the 3D spectra with ML techniques (such as CNN for supervised or self-supervised classifications).
In this workshop held at ENS-Lyon, we aim to bring experts in computing ML, and users of 3D hyperspectral data in order to share expertise around the techniques of 3D classification.
We particularly encourage contributions from young researchers in France or with ties to the French community to present their work. Registration is free of charge. We have limited funds to support travel to Lyon -- please ask when registering if needed.
Presentations will be in English and in-person only, i.e. not remotely. Please note that if you want to give a talk, you need to submit an abstract after registration, i.e. it is not enough to just register your participation in the conference.
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