One of the most widely used approaches in the context of object recognition across illumination changes consists in comparing the images by means of the intersection between invar...
Object localization and classification are important problems in computer vision.
However, in many applications, exhaustive search over all class labels and image
locations is co...
We present an approach for the supervised online learning of object representations based on a biologically motivated architecture of visual processing. We use the output of a rece...
Visual domain adaptation addresses the problem of adapting the sample distribution of the source domain to the target domain, where the recognition task is intended but the data d...
We present a biologically motivated architecture for object recognition that is based on a hierarchical feature-detection model in combination with a memory architecture that impl...