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» Learning from Multiple Annotators with Gaussian Processes
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SIGIR
2008
ACM
13 years 7 months ago
Learning from labeled features using generalized expectation criteria
It is difficult to apply machine learning to new domains because often we lack labeled problem instances. In this paper, we provide a solution to this problem that leverages domai...
Gregory Druck, Gideon S. Mann, Andrew McCallum
RAS
2010
216views more  RAS 2010»
13 years 5 months ago
A nonparametric learning approach to range sensing from omnidirectional vision
We present a novel approach to estimating depth from single omnidirectional camera images by learning the relationship between visual features and range measurements available dur...
Christian Plagemann, Cyrill Stachniss, Jürgen...
ICCV
2011
IEEE
12 years 7 months ago
Incremental On-line Semi-supervised Learning for Segmenting the Left Ventricle of the Heart from Ultrasound Data
Recently, there has been an increasing interest in the investigation of statistical pattern recognition models for the fully automatic segmentation of the left ventricle (LV) of t...
Gustavo Carneiro, Jacinto C. Nascimento
CIVR
2007
Springer
157views Image Analysis» more  CIVR 2007»
14 years 1 months ago
Using multiple segmentations for image auto-annotation
Automatic image annotation techniques that try to identify the objects in images usually need the images to be segmented first, especially when specifically annotating image reg...
Jiayu Tang, Paul H. Lewis
EMNLP
2009
13 years 5 months ago
Parser Adaptation and Projection with Quasi-Synchronous Grammar Features
We connect two scenarios in structured learning: adapting a parser trained on one corpus to another annotation style, and projecting syntactic annotations from one language to ano...
David A. Smith, Jason Eisner