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» MuFeSaC: Learning When to Use Which Feature Detector
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ICANN
2009
Springer
14 years 3 months ago
Learning Features by Contrasting Natural Images with Noise
Abstract. Modeling the statistical structure of natural images is interesting for reasons related to neuroscience as well as engineering. Currently, this modeling relies heavily on...
Michael Gutmann, Aapo Hyvärinen
IJCAI
2007
13 years 10 months ago
A Subspace Kernel for Nonlinear Feature Extraction
Kernel based nonlinear Feature Extraction (KFE) or dimensionality reduction is a widely used pre-processing step in pattern classification and data mining tasks. Given a positive...
Mingrui Wu, Jason D. R. Farquhar
ETRA
2010
ACM
176views Biometrics» more  ETRA 2010»
14 years 4 months ago
Learning relevant eye movement feature spaces across users
In this paper we predict the relevance of images based on a lowdimensional feature space found using several users’ eye movements. Each user is given an image-based search task,...
Zakria Hussain, Kitsuchart Pasupa, John Shawe-Tayl...
IJON
2010
139views more  IJON 2010»
13 years 7 months ago
Event monitoring via local motion abnormality detection in non-linear subspace
We present a computational approach to abnormal visual event detection, which is based on exploring and modeling local motion patterns in a non-linear subspace. We use motion vect...
Ioannis Tziakos, Andrea Cavallaro, Li-Qun Xu
ICASSP
2011
IEEE
13 years 27 days ago
Online feature selection and classification
This paper presents an online feature selection and classification algorithm. The algorithm is implemented for impact acoustics signals to sort hazelnut kernels. The classifier, w...
Habil Kalkan, Bayram Cetisli