Toward Integrated Scene Text Reading von Weinman, Jerod J., Butler, Zachary, Knoll, Dugan, Feild, Jacqueline

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Scene Text Recognition Using Similarity and a Lexicon with Sparse Belief Propagation von Weinman, J.J., Learned-Miller, E., Hanson, A.R.

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On Learning Conditional Random Fields for Stereo: Exploring Model Structures and Approximate Inference von Pal, Christopher J., Weinman, Jerod J., Tran, Lam C., Scharstein, Daniel

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On Learning Conditional Random Fields for Stereo von Pal, Christopher J, Weinman, Jerod J, Tran, Lam C, Scharstein, Daniel

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Typographical Features for Scene Text Recognition von Weinman, Jerod J

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On Learning Conditional Random Fields for Stereo: Exploring Model Structures and Approximate Inference: Structured Prediction and Inference von PAL, Christopher J, WEINMAN, Jerod J, TRAN, Lam C, SCHARSTEIN, Daniel

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Scene Text Recognition Using Similarity and a Lexicon with Sparse Belief Propagation : Probabilistic graphical models von WEINMAN, Jerod J, LEARNED-MILLER, Erik, HANSON, Allen R

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Toward Integrated Scene Text Reading von Weinman, Jerod J, Butler, Zachary, Knoll, Dugan, Feild, Jacqueline

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A discriminative semi-Markov model for robust scene text recognition von Weinman, J.J., Learned-Miller, E., Hanson, A.

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Improving Recognition of Novel Input with Similarity von Weinman, J.J., Learned-Miller, E.

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Efficiently Learning Random Fields for Stereo Vision with Sparse Message Passing von Weinman, Jerod J., Tran, Lam, Pal, Christopher J.

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Chapter 19 - Large-Scale Machine Learning von Weinman, Jerod J., Lidaka, Augustus, Aggarwal, Shitanshu

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Techniques and Applications for Persistent Backgrounding in a Humanoid Torso Robot von Duhon, D.W., Weinman, J.J., Learned-Miller, E.

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SIGN DETECTION IN NATURAL IMAGES WITH CONDITIONAL RANDOM FIELDS von WEINMAN, Jerod, HANSON, Allen, MCCALLUM, Andrew

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Nonlinear Diffusion Scale-Space and Fast Marching Level Sets for Segmentation of MR Imagery and Volume Estimation of Stroke Lesions von Weinman, Jerod, Bissias, George, Horowitz, Joseph, Riseman, Edward, Hanson, Allen

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