The objective of this paper is to study the existing methods for unsupervised object recognition and image categorization and propose a model that can learn directly from the outp...
There are many computer vision algorithms developed for visual (scene and object) recognition. Some systems focus on involved learning algorithms, some leverage millions of trainin...
Abstract. Humans have the remarkable ability to generalize from binocular to monocular figure-ground segmentation of complex scenes. This is clearly evident anytime we look at a p...
Brian Mingus, Trent Kriete, Seth A. Herd, Dean Wya...
Localizing objects in images is a difficult task and represents the first step to the solution of the object recognition problem. This paper presents a novel approach to the local...
In real life, visual learning is supposed to be a continuous process. Humans have an innate facility to recognize objects even under less-than-ideal conditions and to build robust ...