In this paper we propose a novel general framework for unsupervised model adaptation. Our method is based on entropy which has been used previously as a regularizer in semi-superv...
Ariya Rastrow, Frederick Jelinek, Abhinav Sethy, B...
Recognition and encoding of digitized historical documents is still a challenging and difficult task. A major problem is the occurrence of unknown glyphs and symbols which might n...
Choosing an appropriate kernel is one of the key problems in kernel-based methods. Most existing kernel selection methods require that the class labels of the training examples ar...
Abstract. For real time object recognition and tracking often color-based methods are used. While these methods are very efficient, they usually dependent heavily on lighting cond...
Thilo Weigel, Dapeng Zhang 0002, Klaus Rechert, Be...
Recently, there have been several advances in the machine learning and pattern recognition communities for developing manifold learning algorithms to construct nonlinear low-dimen...