Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech t...
Andrew McCallum, Dayne Freitag, Fernando C. N. Per...
From the recovery of structure from motion to the separation of style and content, many problems in computer vision have been successfully approached by using bilinear models. The...
Extracting human postural information from video sequences has proved a difficult research question. The most successful approaches to date have been based on particle filtering, ...
A new method of estimating some statistical characteristics of TCP flows in the Internet is developed in this paper. For this purpose, a new set of random variables (referred to as...
— We derive the theoretical performance of three bio-inspired odor source localization algorithms (casting, surgespiral and surge-cast) in laminar wind flow. Based on the geomet...