Despite a rapid decrease in the price of solid state memory devices, system memory is still a very precious resource in embedded systems. The use of shared libraries is known to b...
Rigorous runtime analyses of evolutionary algorithms (EAs) mainly investigate algorithms that use elitist selection methods. Two algorithms commonly studied are Randomized Local S...
Edda Happ, Daniel Johannsen, Christian Klein, Fran...
Local invariant feature based methods have been proven to be effective in computer vision for object recognition and learning. But for an image, the number of points detected and ...
Recent advances in three-dimensional (3D) data acquisition techniques have offered an alternative to the traditional 2D metamorphosis (or morphing) approaches, which gradually cha...
We present a method to learn and recognize object class models from unlabeled and unsegmented cluttered scenes in a scale invariant manner. Objects are modeled as flexible constel...