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» Learning to Classify X-Ray Images Using Relational Learning
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ACCV
2009
Springer
14 years 3 months ago
Levels of Details for Gaussian Mixture Models
Mixtures of Gaussians are a crucial statistical modeling tool at the heart of many challenging applications in computer vision and machine learning. In this paper, we first descri...
Vincent Garcia, Frank Nielsen, Richard Nock
WWW
2004
ACM
14 years 9 months ago
Is question answering an acquired skill?
We present a question answering (QA) system which learns how to detect and rank answer passages by analyzing questions and their answers (QA pairs) provided as training data. We b...
Ganesh Ramakrishnan, Soumen Chakrabarti, Deepa Par...
ICIAP
2009
ACM
14 years 1 months ago
Applying Visual Object Categorization and Memory Colors for Automatic Color Constancy
This paper presents a framework for using high-level visual information to enhance the performance of automatic color constancy algorithms. The approach is based on recognizing spe...
Esa Rahtu, Jarno Nikkanen, Juho Kannala, Leena Lep...
CVPR
2005
IEEE
14 years 10 months ago
Tangent-Corrected Embedding
Images and other high-dimensional data can frequently be characterized by a low dimensional manifold (e.g. one that corresponds to the degrees of freedom of the camera). Recently,...
Ali Ghodsi, Jiayuan Huang, Finnegan Southey, Dale ...
SADM
2010
141views more  SADM 2010»
13 years 3 months ago
A parametric mixture model for clustering multivariate binary data
: The traditional latent class analysis (LCA) uses a mixture model with binary responses on each subject that are independent conditional on cluster membership. However, in many pr...
Ajit C. Tamhane, Dingxi Qiu, Bruce E. Ankenman