This paper considers the problems of feature variation and concept uncertainty in typical learning-based video semantic classification schemes. We proposed a new online semantic c...
We present an interactive system, which allows the user to produce drawings in a variety of traditional styles. It takes as input an image and performs semi-automatic tonal modelin...
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
This research presents an integrated simulation modelingDesign For Six Sigma (DFSS) framework to study the design and process issues in a server manufacturing environment. The ser...
Sreekanth Ramakrishnan, Pei-Fang Tsai, Christiana ...
Neural activity is non-stationary and varies across time. Hidden Markov Models (HMMs) have been used to track the state transition among quasi-stationary discrete neural states. W...
Kentaro Katahira, Jun Nishikawa, Kazuo Okanoya, Ma...