Boosting methods are known not to usually overfit training data even as the size of the generated classifiers becomes large. Schapire et al. attempted to explain this phenomenon i...
The naive classifier is a well-established mathematical model whose simplicity, speed and accuracy have made it a popular choice for classification in AI and engineering. In this ...
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...
Diffusion-Tensor MRI can be used to measure fibre orientation within the brain. Several studies have proposed methods to reconstruct known white matter fibre tracts in the brain. ...
Philip A. Cook, Daniel C. Alexander, Geoffrey J. M...
Point Distribution Modelling (PDM) is an efficient generative technique that can be used to incorporate statistical shape priors into image analysis methods like Active Shape Mode...
Alejandro F. Frangi, Loic Boisrobert, Marcos Lauce...