Learning Bayesian networks from data is an N-P hard problem with important practical applications. Several researchers have designed algorithms to overcome the computational comple...
Design and development of novel human-computer interfaces poses a challenging problem: actions and intentions of users have to be inferred from sequences of noisy and ambiguous mu...
Vladimir Pavlovic, James M. Rehg, Ashutosh Garg, T...
This work extends and improves a recently introduced (Dec. 2007) dynamic Bayesian network (DBN) based audio-visual automatic speech recognition (AVASR) system. That system models ...
It is generally acknowledged that macroinvertebrates are good indicators of water quality in streams, as a number of taxa are sensitive to pollution and integrate their response t...