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Topic: Formulating Semantic Image Annotation as a Supervised Learning Problem
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 Person was signed in when posted  4
05-17-2008 04:59 AM ET (US)
Deleted by topic administrator 05-17-2008 10:16 AM
Anup Doshi  3
11-03-2005 03:31 PM ET (US)
My favorite question...why did they choose the DCT as the feature set, and would this formulation work better with a different set of 'words'?
Brendan Morris  2
11-03-2005 01:54 PM ET (US)
I'm fuzzy on the unsupervised learning and what the hidden states L correlate to in this problem. The annotation results are quite impressive. I'm curious what percentage of the dataset had recall = 0 and what might be the reasons for this.

As a side note it's amazing how taking Vasconcelos class helps understand the Bayesian formulation.
Robin Hewitt  1
11-03-2005 10:14 AM ET (US)
How are the authors choosing the value for K in the EM algorithm...is K set to the number of semantic concepts?
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