The Gaussian mixture model is a powerful statistical tool in data modeling and analysis. Generally, the EM algorithm is utilized to learn the parameters of the Gaussian mixture. Ho...
Restricted Boltzmann Machines (RBM) are well-studied generative models. For image data, however, standard RBMs are suboptimal, since they do not exploit the local nature of image ...
In the present paper, we address the problem of recovering the true underlying model of a surface while performing the segmentation. A novel criterion for surface (model) selection...
We present an approach that combines bag-of-words and spatial models to perform semantic and syntactic analysis for recognition of an object based on its internal appearance and i...
Controlling a tendon-driven robot like the humanoid Ecce is a difficult task, even more so when its kinematics and its pose are not known precisely. In this paper, we present a vis...