—This paper proposes a probabilistic technique that enables a node to estimate the number of its neighbors that fulfill certain criteria. The technique does not require any a pr...
Helmut Adam, Evsen Yanmaz, Wilfried Elmenreich, Ch...
Probabilistic feature relevance learning (PFRL) is an effective method for adaptively computing local feature relevance in content-based image retrieval. It computes flexible retr...
A prerequisite to calibrated camera pose estimation is the construction of a camera neighborhood adjacency graph, a connected graph defining the pose neighbors of the camera set....
Probabilistic feature relevance learning (PFRL) is an effective technique for adaptively computing local feature relevance for content-based image retrieval. It however becomes le...
Abstract. Estimating the degree of similarity between images is a challenging task as the similarity always depends on the context. Because of this context dependency, it seems qui...