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» Testing of Image Processing Algorithms on Synthetic Data
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DAGM
2004
Springer
15 years 10 months ago
Learning from Labeled and Unlabeled Data Using Random Walks
We consider the general problem of learning from labeled and unlabeled data. Given a set of points, some of them are labeled, and the remaining points are unlabeled. The goal is to...
Dengyong Zhou, Bernhard Schölkopf
149
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ICML
2010
IEEE
15 years 5 months ago
Local Minima Embedding
Dimensionality reduction is a commonly used step in many algorithms for visualization, classification, clustering and modeling. Most dimensionality reduction algorithms find a low...
Minyoung Kim, Fernando De la Torre
MICCAI
2010
Springer
15 years 3 months ago
Multi-Class Sparse Bayesian Regression for Neuroimaging Data Analysis
The use of machine learning tools is gaining popularity in neuroimaging, as it provides a sensitive assessment of the information conveyed by brain images. In particular, finding ...
Vincent Michel, Evelyn Eger, Christine Keribin, Be...
ISBI
2006
IEEE
16 years 5 months ago
Molecular image registration using mutual information and differential evolution optimization
In this work we propose a novel rigid image registration approach to determine the position of high-resolution molecular structures in medium-resolution macromolecular complexes. ...
Bartosz Telenczuk, María J. Ledesma-Carbayo...
PSIVT
2009
Springer
400views Multimedia» more  PSIVT 2009»
15 years 11 months ago
Local Image Descriptors Using Supervised Kernel ICA
PCA-SIFT is an extension to SIFT which aims to reduce SIFT’s high dimensionality (128 dimensions) by applying PCA to the gradient image patches. However PCA is not a discriminati...
Masaki Yamazaki, Sidney Fels