We investigate maximum likelihood parameter learning in Conditional Random Fields (CRF) and present an empirical study of pseudo-likelihood (PL) based approximations of the paramet...
Abstract. Probabilistic models with hidden variables such as probabilistic Latent Semantic Analysis (pLSA) and Latent Dirichlet Allocation (LDA) have recently become popular for so...
The design of inference algorithms for discrete-valued Markov Random Fields constitutes an ongoing research topic in computer vision. Large state-spaces, none-submodular energy-fun...
Abstract. High-speed image measurements of fluid flows define an important field of research in experimental fluid mechanics and the related industry. Numerous competing methods ha...
This work focuses on tomographic image reconstruction in experimental fluid mechanics (TomoPIV), a recently established 3D particle image velocimetry technique. Corresponding 2D im...