Learning to Parse Images

We describe a class of probabilistic models that we call credibility networks. Using parse trees as internal representations of images, credibility networks are able to perform segmentation and recog(cid:173) nition simultaneously, removing the need for ad hoc segmentation heuristics. Promising results in the problem of segmenting hand(cid:173) written digits were obtained.