Modeling spatial context (e.g., autocorrelation) is a key challenge in classification problems that arise in geospatial domains. Markov random fields (MRF) is a popular model for i...
Shashi Shekhar, Paul R. Schrater, Ranga Raju Vatsa...
We present a variational Bayesian framework for performing inference, density estimation and model selection in a special class of graphical models--Hidden Markov Random Fields (H...
Li Cheng, Feng Jiao, Dale Schuurmans, Shaojun Wang
This paper proposes to combine spatial and color coherency with the pixel-wise GMM to determine the background model. We first represent each pixel with a hybrid feature vector, w...
Abstract. We propose a deep study on tissue modelization and classification Techniques on T1-weighted MR images. Three approaches have been taken into account to perform this valid...
Convolutional networks have achieved a great deal of success in high-level vision problems such as object recognition. Here we show that they can also be used as a general method ...
Viren Jain, Joseph F. Murray, Fabian Roth, Sriniva...