Journal ArticleDOI
Floating search methods in feature selection
TLDR
Sequential search methods characterized by a dynamically changing number of features included or eliminated at each step, henceforth "floating" methods, are presented and are shown to give very good results and to be computationally more effective than the branch and bound method.About:
This article is published in Pattern Recognition Letters.The article was published on 1994-11-01. It has received 3104 citations till now. The article focuses on the topics: Beam search & Jump search.read more
Citations
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Journal ArticleDOI
Real-time hyperspectral processing for automatic nonferrous material sorting
TL;DR: The approach behind the integration of the spectral and spatial information in the material classification process is reengineered to allow the real-time sorting of the nonferrous fractions that are contained in the waste of electric and electronic equipment scrap.
Journal ArticleDOI
Liver fibrosis staging using CT image texture analysis and soft computing
Omer Kayaalti,Bekir Hakan Aksebzeci,Ibrahim Karahan,Kemal Deniz,Mehmet Adnan Ozturk,Bulent Yilmaz,Sadık Kara,Musa H. Asyali +7 more
TL;DR: A non-invasive, low-cost and relatively accurate method was developed to determine liver fibrosis stage by analyzing some texture features of liver CT images and showed that DWT, Gabor, GLCM, and Laws' texture features were more successful than the others; as such features extracted from these methods were used in the feature fusion process.
Journal ArticleDOI
Feature selection for HMM and BLSTM based handwriting recognition of whiteboard notes
Marcus Liwicki,Horst Bunke +1 more
TL;DR: In this paper, feature selection experiments for online handwriting recognition were described, and a set of 25 online and pseudo-offline features were investigated to find out which features are important.
Book ChapterDOI
Color Texture Classification by Wavelet Energy Correlation Signatures
TL;DR: This paper introduces wavelet energy-correlation signatures and the transformation of these signatures upon linear color space transformations is derived and it is demonstrated that the wavelet correlation features contain more information than the intensity or the energy features of each color plane separately.
References
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Journal ArticleDOI
A Branch and Bound Algorithm for Feature Subset Selection
TL;DR: In this paper, a branch and bound-based feature subset selection algorithm is proposed to select the best subset of m features from an n-feature set without exhaustive search, which is computationally computationally unfeasible.
Journal ArticleDOI
A note on genetic algorithms for large-scale feature selection
W. Siedlecki,Jack Sklansky +1 more
TL;DR: The preliminary results suggest that GA is a powerful means of reducing the time for finding near-optimal subsets of features from large sets.
Journal ArticleDOI
A Direct Method of Nonparametric Measurement Selection
TL;DR: A direct method of measurement selection is proposed to determine the best subset of d measurements out of a set of D total measurements, using a nonparametric estimate of the probability of error given a finite design sample set.
Journal ArticleDOI
On the effectiveness of receptors in recognition systems
T. Marill,D. Green +1 more
TL;DR: Some of the theoretical problems encountered in trying to determine a more formal measure of the effectiveness of a set of tests are discussed; a measure which might be a practical substitute for the empirical evaluation.
Journal ArticleDOI
On automatic feature selection
W. Siedlecki,Jack Sklansky +1 more
TL;DR: In this paper, a review of feature selection for multidimensional pattern classification is presented, and the potential benefits of Monte Carlo approaches such as simulated annealing and genetic algorithms are compared.