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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...)     Options: All Media Types Journals Proceedings Div Books Whole Books Other Date Reviewed Title Author Publisher Published Date Descending Ascending     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       Display 510152550100 per page
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