We introduce a family of unsupervised algorithms, numerical taxonomy clustering, to simultaneously cluster data, and to learn a taxonomy that encodes the relationship between the ...
We propose an image segmentation algorithm that is based on spatially adaptive color and texture features. The features are first developed independently, and then combined to obt...
Junqing Chen, Thrasyvoulos N. Pappas, Aleksandra M...
Recent advances in 4D imaging and real-time imaging provide image data with clinically important cardiac dynamic information at high spatial or temporal resolution. However, the en...
While spectral clustering has been applied successfully to problems in computer vision, their applicability is limited to pairwise similarity measures that form a probability matr...
EEG segments recorded during microsleep events were transformed to the frequency domain and were subsequently clustered without the common summation of power densities in spectral ...