We propose an algorithm that groups points similarly to how human observers do. It is simple, totally unsupervised and able to find clusters of complex and not necessarily convex s...
We present a query-by-example audio retrieval framework by indexing audio clips in a generic database as points in a latent perceptual space. First, feature-vectors extracted from...
A novel unsupervised clustering algorithm called Hyperclique Pattern-KMEANS (HP-KMEANS) is presented. Considering recent success in semisupervised clustering using pair-wise const...
Yuchou Chang, Dah-Jye Lee, James K. Archibald, Yi ...
We use cluster analysis as a unifying principle for problems from low, middle and high level vision. The clustering problem is viewed as graph partitioning, where nodes represent ...