Tracking over a long period of time is challenging as the appearance, shape and scale of the object in question may vary. We propose a paradigm of tracking by repeatedly segmentin...
The power and popularity of kernel methods stem in part from their ability to handle diverse forms of structured inputs, including vectors, graphs and strings. Recently, several m...
Darrin P. Lewis, Tony Jebara, William Stafford Nob...
Universities and Institutions these days’ deals with issues related to with assessment of large number of students. Various evaluation methods have been adopted by examiners in ...
Ahmed Barnawi, Abdurrahman H. Al-Talhi, M. Rizwan ...
We describe a neurally-inspired, unsupervised learning algorithm that builds a non-linear generative model for pairs of face images from the same individual. Individuals are then ...
Kernel classifiers based on Support Vector Machines (SVM) have recently achieved state-of-the art results on several popular datasets like Caltech or Pascal. This was possible by...