Variations
One variation that attempts to reduce complexity is the star model proposed by Fergus et al. The reduced dependencies of this model allows for learning in time instead of . This allows for a greater number of model parts and image features to be used in training. Because the star model has fewer parameters, it is also better at avoiding the problem of over-fitting when trained on fewer images.
Read more about this topic: Constellation Model
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