We propose an unsupervised, probabilistic method for learning visual feature hierarchies. Starting from local, low-level features computed at interest point locations, the method c...
1 We present a functional data analysis (FDA) based method to statistically model continuous signs of the American Sign Language (ASL) for use in the recognition of signs in contin...
Background: The Clinical E-Science Framework (CLEF) project has built a system to extract clinically significant information from the textual component of medical records in order...
Angus Roberts, Robert J. Gaizauskas, Mark Hepple, ...
Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...
The development of the XCS Learning Classifier System has produced a robust and stable implementation that performs competitively in direct-reward environments. Although investig...