Remote sensing observations play an important role in the geo- and bioscientific community, since they enable various applications to accurately monitor the Earth and its changes - on a microscopic level as well as from space. Observation systems regularly provide data with a spectrally, spatially and temporally high resolution. Beside the challenge to deal with large amounts of data and limited class label information, current and future challenges comprise the definition and the way of integration of prior and domain knowledge, the learning of sophisticated features and the fusion of multiple sensor data. This talk will cover several remote sensing applications which are addressed in my group, and I will present my vision of future methods to learn better models of complex geo- and biophysical processes and phenomena.
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