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» Protein Classification with Multiple Algorithms
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CVPR
2009
IEEE
16 years 4 months ago
Let the Kernel Figure it Out; Principled Learning of Pre-processing for Kernel Classifiers
Most modern computer vision systems for high-level tasks, such as image classification, object recognition and segmentation, are based on learning algorithms that are able to se...
Peter V. Gehler, Sebastian Nowozin
IJCNN
2008
IEEE
15 years 4 months ago
Filter Bank Common Spatial Pattern (FBCSP) in Brain-Computer Interface
—In motor imagery-based Brain Computer Interfaces (BCI), discriminative patterns can be extracted from the electroencephalogram (EEG) using the Common Spatial Pattern (CSP) algor...
Kai Keng Ang, Zhang Yang Chin, Haihong Zhang, Cunt...
VLSISP
2011
358views Database» more  VLSISP 2011»
14 years 4 months ago
Accelerating Machine-Learning Algorithms on FPGAs using Pattern-Based Decomposition
Machine-learning algorithms are employed in a wide variety of applications to extract useful information from data sets, and many are known to suffer from superlinear increases in ...
Karthik Nagarajan, Brian Holland, Alan D. George, ...
ICALT
2005
IEEE
15 years 3 months ago
The Effect of Correlation on the Accuracy of Meta-Learning Approach
Meta-learning is an efficient approach in the field of machine learning, which involves multiple classifiers. In this paper, a meta-learning framework consisting of stacking meta-...
Li-ying Yang, Zheng Qin
67
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IPMI
2003
Springer
15 years 10 months ago
Expectation Maximization Strategies for Multi-atlas Multi-label Segmentation
It is well-known in the pattern recognition community that the accuracy of classifications obtained by combining decisions made by independent classifiers can be substantially high...
Torsten Rohlfing, Daniel B. Russakoff, Calvin R. M...