Machine learning often relies on costly labeled data, and this impedes its application to new classification and information extraction problems. This has motivated the developme...
In this work, we are concerned with the detection of multiple objects in an image. We demonstrate that typically applied objectives have the structure of a random field model, but...
Behavioral synthesis tools have made significant progress in compiling high-level programs into register-transfer level (RTL) specifications. But manually rewriting code is still ...
Non-negative spectrogram factorization algorithms such as probabilistic latent component analysis (PLCA) have been shown to be quite powerful for source separation. When training d...
We present a novel approach for analyzing two-dimensional (2D) flow field data based on the idea of invariant moments. Moment invariants have traditionally been used in computer vi...
Michael Schlemmer, Manuel Heringer, Florian Morr...