A Bayesian ensemble learning method is introduced for unsupervised extraction of dynamic processes from noisy data. The data are assumed to be generated by an unknown nonlinear ma...
n explore and understand abstract information spaces as if they were real geographic spaces. According to the distance-similarity metaphor1 one of the most popular spatial metaphor...
Sara Irina Fabrikant, Daniel R. Montello, David M....
As the number of digital images is growing fast and Content-based Image Retrieval (CBIR) is gaining in popularity, CBIR systems should leap towards Webscale datasets. In this paper...
Michal Batko, Fabrizio Falchi, Claudio Lucchese, D...
The prediction of protein function as well as the reconstruction of evolutionary genesis employing sequence comparison at large is still the most powerful tool in sequence analysi...
Abstract. A model of human appearance is presented for efficient pose estimation from real-world images. In common with related approaches, a high-level model defines a space of co...
Timothy J. Roberts, Stephen J. McKenna, Ian W. Ric...