Recent
April 2013 My colleagues and I have recently gotten our paper Augmenting CRFs with Boltzmann Machine Shape Priors for Image Labeling accepted at CVPR 2013!
2012 My colleagues and I have published our JMLR paper Bounding the Probability of Error for High Precision Optical Character Recognition.
All Papers
- Andrew Kae*, Kihyuk Sohn*, Honglak Lee, and Erik Learned-Miller
Augmenting CRFs with Boltzmann Machine Shape Priors for Image Labeling.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2013..
*The first and second authors made equal contributions and should be considered co-first authors.
[pdf] [data] [project page] - Gary B. Huang, Andrew Kae, Carl Doersch, and Erik Learned-Miller
Bounding the Probability of Error for High Precision Optical Character Recognition.
Journal of Machine Learning Research (JMLR), 2012.
[pdf] - Andrew Kae, Kin Kan, Vijay K Narayanan, Dragomir Yankov
Categorization of Display Ads using Image and Landing Page Features
The Third Workshop on Large-scale Data Mining: Theory and Applications'11 (LDMTA'11), in conjunction with SIGKDD2011.
[pdf]
- Andrew Kae, David A. Smith, and Erik Learned-Miller
Learning on the Fly: A font-free approach towards multilingual OCR
International Journal on Document Analysis and Recognition (IJDAR), 2011.
[pdf] [Springer]
- Andrew Kae, Gary Huang, Carl Doersch, and Erik Learned-Miller
Improving State-of-the-Art OCR through High-Precision Document-Specific Modeling
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2010.
[pdf]
- Andrew Kae, Gary Huang, and Erik Learned-Miller
Bounding the Probability of Error for High Precision Recognition.
Technical Report UM-CS-2009-031, Dept. of Computer Science, University of Massachusetts, Amherst, 2009.
[pdf] [arxiv.org]
- Andrew Kae and Erik Learned-Miller
Learning on the fly: Font free approaches to difficult OCR problems.
Proceedings of the International Conference on Document Analysis and Recognition (ICDAR), 2009.
[pdf]
