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  Browse All Reviews > Computing Methodologies (I) > Pattern Recognition (I.5) > Design Methodology (I.5.2) > Feature Evaluation And Selection (I.5.2...)  
  1-10 of 39 Reviews about "Feature Evaluation And Selection (I.5.2...)": Date Reviewed
  Feature selection and enhanced krill herd algorithm for text document clustering
Abualigah L., Springer International Publishing, New York, NY, 2019. 165 pp.  Type: Book (978-3-030106-73-7)

This monograph, which comes out of the author’s PhD thesis, studies text document clustering with the help of the krill herd (KH) algorithm....

May 10 2019
  A filter attribute selection method based on local reliable information
Martín R., Aler R., Galván I. Applied Intelligence 48(1): 35-45, 2018.  Type: Article

In classification algorithms, the core problem is selecting the right attributes and assigning them the right weight for each item being processed, in order to achieve reliable results; all the more so if machine learning is involved. ...

Apr 25 2018
   Tied factors analysis for high-dimensional image feature extraction and recognition application
Liao H., Chen Y., Dai W., Ruan R. Pattern Analysis & Applications 20(2): 587-600, 2017.  Type: Article

Face recognition is one of those unstructured tasks that the human brain excels at, but that is difficult for computers to perform. But as it becomes crucial for many modern activities, it would be a great help for us humans if we coul...

Jun 15 2017
  Context-based unsupervised ensemble learning and feature ranking
Soltanmohammadi E., Naraghi-Pour M., van der Schaar M. Machine Learning 105(3): 459-485, 2016.  Type: Article

An unsupervised ensemble learning and feature ranking method in which the combiner has no information about the expert’s performance, methods, and the data with which they operate is proposed in this paper. The method uses ba...

Apr 20 2017
  Variational Bayesian inference for infinite generalized inverted Dirichlet mixtures with feature selection and its application to clustering
Bdiri T., Bouguila N., Ziou D. Applied Intelligence 44(3): 507-525, 2016.  Type: Article

Model-based data analysis is a powerful, increasingly popular tool for inferring knowledge and abstract information from data sets. To date, the model-based learning literature has mostly been dominated by Gaussian mixtures. However, c...

Jun 20 2016
  A comprehensive performance evaluation of 3D local feature descriptors
Guo Y., Bennamoun M., Sohel F., Lu M., Wan J., Kwok N. International Journal of Computer Vision 116(1): 66-89, 2016.  Type: Article

For those that are working with 3D point clouds (for example, 3D keypoint detection, 3D local feature descriptors, 3D object recognition/classification/retrieval, 3D scene modeling and reconstruction, and 3D data registration, among ma...

Apr 27 2016
  Face and palmprint multimodal biometric systems using Gabor-Wigner transform as feature extraction
Saini N., Sinha A. Pattern Analysis & Applications 18(4): 921-932, 2015.  Type: Article

Biometric identification of humans has many compelling advantages, but some challenges must be overcome. Each biometric modality (face, fingerprint, iris, and so on) has some number of individuals for which it is difficult to apply or ...

Feb 9 2016
  Multi-modal biological driver monitoring via ubiquitous wearable body sensor network
Dehzangi O., Williams C.  DH 2015 (Proceedings of the 5th International Conference on Digital Health 2015, Florence, Italy, May 18-20, 2015) 65-70, 2015.  Type: Proceedings

Self-driving cars, or driverless cars, are becoming the future of driving without manual intervention. Currently, the speed of around 25 kilometers per hour (km/h) has been achieved for self-driving cars; however, the research in this ...

Aug 20 2015
  Feature selection for data and pattern recognition
Stanczyk U., Jain L., Springer Publishing Company, Incorporated, New York, NY, 2014. 355 pp.  Type: Book (978-3-662456-19-4)

Feature selection is one of the most important preprocessing steps, with the performance of any system designed to solve pattern recognition, or data mining tasks in general, being strongly dependent on the quality of the feature set i...

Jun 16 2015
  SVD-based feature extraction from time-series motion data and its application to gesture recognition
Hayashi I., Jiang Y., Wang S.  BICT 2014 (Proceedings of the 8th International Conference on Bioinspired Information and Communications Technologies, Boston, MA, Dec 1-3, 2014) 386-387, 2014.  Type: Proceedings, Reviews: (2 of 2)

Hayashi et al. describe an innovative use of singular value decomposition (SVD) techniques to explore feature extraction and gesture recognition in this proceedings paper. It provides a nice presentation with respect to SVD decompositi...

May 26 2015
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