Conventional subspace learning or recent feature extraction methods consider globality as the key criterion to design discriminative algorithms for image classification. We demonst...
Yun Fu, Zhu Li, Junsong Yuan, Ying Wu, Thomas S. H...
In this paper we study supervised and semi-supervised classification of e-mails. We consider two tasks: filing e-mails into folders and spam e-mail filtering. Firstly, in a sup...
Irena Koprinska, Josiah Poon, James Clark, Jason C...
Background: The identification of relevant biological features in large and complex datasets is an important step towards gaining insight in the processes underlying the data. Oth...
Yvan Saeys, Sven Degroeve, Dirk Aeyels, Pierre Rou...
ir increasing use of abstraction, modularity, delayed binding, polymorphism, and source reuse, especially when these attributes are used in combination. Modern processor architectu...
Hemant G. Rotithor, Kevin W. Harris, Mark W. Davis
—It is well-known that the linear scale-space theory in computer vision is mainly based on the Gaussian kernel. The purpose of the paper is to propose a scale-space theory based ...