Learning to Parse Images

Part of Advances in Neural Information Processing Systems 12 (NIPS 1999)

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Geoffrey E. Hinton, Zoubin Ghahramani, Yee Whye Teh


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.