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CVPR
2010
IEEE
15 years 11 months ago
Improving State-of-the-Art OCR through High-Precision Document-Specific Modeling
Optical character recognition (OCR) remains a difficult problem for noisy documents or documents not scanned at high resolution. Many current approaches rely on stored font models...
Andrew Kae, Gary Huang, Erik Learned-miller, Carl ...
CVPR
2009
IEEE
16 years 10 months ago
Towards Total Scene Understanding: Classification, Annotation and Segmentation in an Automatic Framework
Given an image, we propose a hierarchical generative model that classifies the overall scene, recognizes and segments each object component, as well as annotates the image with ...
Fei-Fei Li 0002, Li-Jia Li, Richard Socher
124
Voted
ICML
2009
IEEE
16 years 3 months ago
Structure learning of Bayesian networks using constraints
This paper addresses exact learning of Bayesian network structure from data and expert's knowledge based on score functions that are decomposable. First, it describes useful ...
Cassio Polpo de Campos, Zhi Zeng, Qiang Ji
112
Voted
MT
2002
118views more  MT 2002»
15 years 2 months ago
MT for Minority Languages Using Elicitation-Based Learning of Syntactic Transfer Rules
The AVENUE project contains a run-time machine translation program that is surrounded by pre- and post-run-time modules. The post-run-time module selects among translation alternat...
Katharina Probst, Lori S. Levin, Erik Peterson, Al...
127
Voted
PAMI
2010
181views more  PAMI 2010»
15 years 1 months ago
Using Language to Learn Structured Appearance Models for Image Annotation
Abstract— Given an unstructured collection of captioned images of cluttered scenes featuring a variety of objects, our goal is to simultaneously learn the names and appearances o...
Michael Jamieson, Afsaneh Fazly, Suzanne Stevenson...