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Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P. and Witten, I. (2009) The Weka Data Mining Software: An Update. ACM SIGKDD Explorations Newsletter, 11, 10-18.
http://www.cs.waikato.ac.nz/ml/weka/
http://dx.doi.org/10.1145/1656274.1656278

has been cited by the following article:

• TITLE: Mexican Sign Language Recognition Using Jacobi-Fourier Moments

  AUTHORS: Francisco Solís, Carina Toxqui, David Martínez

  KEYWORDS: Mexican Sign Language, Jacobi-Fourier Moments, Digital Image Processing

  JOURNAL NAME: Engineering, Vol.7 No.10, October 30, 2015

  ABSTRACT: The present work introduces a system for recognizing static signs in Mexican Sign Language (MSL) using Jacobi-Fourier Moments (JFMs) and Artificial Neural Networks (ANN). The original color images of static signs are cropped, segmented and converted to grayscale. Then to reduce computational costs 64 JFMs were calculated to represent each image. The JFMs are sorted to select a subset that improves recognition according to a metric proposed by us based on a ratio between dispersion measures. Using WEKA software to test a Multilayer-Perceptron with this subset of JFMs reached 95% of recognition rate.