We present a novel clustering method using HMM parameter space and eigenvector decomposition. Unlike the existing methods, our algorithm can cluster both constant and variable leng...
Abstract-- Automatic recognition of activities using time series data collected from exercise can facilitate development of applications that motivate people to exercise more frequ...
Pekka Siirtola, Perttu Laurinen, Eija Haapalainen,...
The classification of urban landscape in aerial LiDAR point clouds is useful in 3D modeling and object recognition applications in urban environments. In this paper, we introduce ...
In this paper, we propose a novel learning method, called Jensen-Shannon Boosting (JSBoost) and demonstrate its application to object recognition. JSBoost incorporates Jensen-Shan...
In data applications such as information integration, there can be limited access patterns to relations, i.e., binding patterns require values to be specified for certain attribut...