The performance of an offline-trained classifier can be improved on-site by adapting the classifier towards newly acquired data. However, the adaptation rate is a tuning parame...
Encouraging exploration, typically by preserving the diversity within the population, is one of the most common method to improve the behavior of evolutionary algorithms with dece...
This paper introduces a novel way to leverage the implicit geometry of sparse local features (e.g. SIFT operator) for the purposes of object detection and segmentation. A two-clas...
— It is widely agreed that efficient visual search requires the integration of target-driven top-down information and image-driven bottom-up information. Yet the problem of gaze...
— This paper describes a method of probabilistic obstacle map building based on Bayesian estimation. Most active or passive obstacle sensors observe only the most frontal objects...