HIGHLIGHTS
- who: (Corresponding Authors Lichao Mou and colleagues from the Institute (IMF), German Aerospace Center (DLR), Germany and with the Signal Processing in Earth Observation), Technical University of Munich have published the research work: Detecting Changes by Learning No Changes: Data-enclosing-ball Minimizing Autoencoders for One-class Change Detection in Multispectral Imagery, in the Journal: (JOURNAL)
- what: The authors propose a novel data-enclosing-ball minimizing autoencoder (DebM-AE) that is trained with dual objectives-a reconstruction error criterion and a minimum volume criterion. To address it, the authors propose a data-enclosingball minimizing autoencoder . . .
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