Bayesian network models are widely used for discriminative prediction tasks such as classification. Usually their parameters are determined using 'unsupervised' methods ...
Abstract. The identification of reliable and interesting items on Internet becomes more and more difficult and time consuming. This paper is a position paper describing our intend...
In this paper, we present a novel localized Markov random field (MRF) method based on superpixels for region segmentation. Early vision problems could be formulated as pixel label...
High compression of plant geometry is an important aspect in fast realistic visualization of plants. Hierarchical structuring plant morphology is a key factor for real time plant r...
Signal modeling lies at the core of numerous signal and image processing applications. A recent approach that has drawn considerable attention is sparse representation modeling, in...