Learning to Parse Images

Hinton, Geoffrey E., Ghahramani, Zoubin, Teh, Yee Whye

Neural Information Processing Systems 

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 recognition simultaneously,removing the need for ad hoc segmentation heuristics. Promising results in the problem of segmenting handwritten digitswere obtained.

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