Search results for " Probabilistic Model."
showing 2 items of 2 documents
Combining Top-down and Bottom-up Visual Saliency for Firearms Localization
2014
Object detection is one of the most challenging issues for computer vision researchers. The analysis of the human visual attention mechanisms can help automatic inspection systems, in order to discard useless information and improving performances and efficiency. In this paper we proposed our attention based method to estimate firearms position in images of people holding firearms. Both top-down and bottom-up mechanisms are involved in our system. The bottom-up analysis is based on a state-of-the-art approach. The top-down analysis is based on the construction of a probabilistic model of the firearms position with respect to the people’s face position. This model has been created by analyzi…
Inverted Repeats in Viral Genomes
2004
We investigate 738 complete genomes of viruses to detect the presence of short inverted repeats. The number of inverted repeats found is compared with the prediction obtained for a Bernoullian and for a Markovian control model. We find as a statistical regularity that the number of observed inverted repeats is often greater than the one expected in terms of a Bernoullian or Markovian model in several of the viruses and in almost all those with a genome longer than 30,000 bp.