A critical problem in clustering research is the definition of a proper metric to measure distances between points. Semi-supervised clustering uses the information provided by the ...
Tumor segmentation from MRI data is an important but time consuming task performed manually by medical experts. Automating this process is challenging due to the high diversity in...
Albert Murtha, Dana Cobzas, Mark Schmidt, Martin J...
Large numbers of dimensions not only cause clutter in multidimensional visualizations, but also make it difficult for users to navigate the data space. Effective dimension manage...
Jing Yang, Wei Peng, Matthew O. Ward, Elke A. Rund...
Developing models and methods to manage data vagueness is a current effervescent research field. Some work has been done with supervised problems but unsupervised problems and unce...
Particle filters have proven to be an effective tool for visual tracking in non-gaussian, cluttered environments. Conventional particle filters however do not scale to the problem...
Jonathan Deutscher, Andrew J. Davison, Ian D. Reid