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
Brain–Computer Communication: Motivation, Aim, and Impact of Exploring a Virtual Apartment
Robert Leeb,Felix Yuan-Tseng Lee,Claudia Keinrath,Reinhold Scherer,Horst Bischof,Gert Pfurtscheller +5 more
TL;DR: This work shows that ten naive subjects can be trained in a synchronous paradigm within three sessions to navigate freely through a virtual apartment, whereby at every junction the subjects could decide by their own, how they wanted to explore the virtual environment (VE).
Journal ArticleDOI
A survey on face detection in the wild
TL;DR: The recent advances in real-world face detection techniques are surveyed, beginning with the seminal Viola-Jones face detector methodology and are roughly categorized into two general schemes: rigid templates, learned mainly via boosting based methods or by the application of deep neural networks, and deformable models that describe the face by its parts.
Journal ArticleDOI
Supervised, Unsupervised, and Semi-Supervised Feature Selection: A Review on Gene Selection
TL;DR: The basic taxonomy of feature selection is presented, and the state-of-the-art gene selection methods are reviewed by grouping the literatures into three categories: supervised, unsupervised, and semi-supervised.
Journal ArticleDOI
Tree species classification in the Southern Alps based on the fusion of very high geometrical resolution multispectral/hyperspectral images and LiDAR data
TL;DR: In this paper, the authors analyzed two multi-sensor set-ups: (1) airborne high spatial resolution hyperspectral images combined with LiDAR data; and (2) high spatial-resolution satellite multispectral image combined with Lidar data.
Proceedings ArticleDOI
Feature level fusion of hand and face biometrics
Arun Ross,Rohin Govindarajan +1 more
TL;DR: This work discusses fusion at the feature level in 3 different scenarios: (i) fusion of PCA and LDA coefficients of face; (ii) Fusion of LDA coefficient corresponding to the R,G,B channels of a face image; and (iii) fusionof face and hand modalities.
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.