We propose a non-linear graphical model for structured prediction. It combines the power of deep neural networks to extract high level features with the graphical framework of Mar...
Impression evidence in the form of shoe-prints are commonly found in crime scenes. A critical step in automatic shoe-print identification is extraction of the shoe-print pattern. ...
The paper describes a lexicon driven approach for word recognition on handwritten documents using Conditional Random Fields(CRFs). CRFs are discriminative models and do not make a...
Shravya Shetty, Harish Srinivasan, Sargur N. Sriha...
Hidden Conditional Random Fields(HCRF) is a very promising approach to model speech. However, because HCRF computes the score of a hypothesis by summing up linearly weighted featu...
Conditional random fields (CRF) are widely used for predicting output variables that have some internal structure. Most of the CRF research has been done on structured classificati...