Naïve Bayesian classifier for human shape recognition

@article{Mahmud2013NaveBC,
  title={Na{\"i}ve Bayesian classifier for human shape recognition},
  author={Ahmad Rodzi Mahmud and N. Md Tahir},
  journal={2013 IEEE 9th International Colloquium on Signal Processing and its Applications},
  year={2013},
  pages={219-223}
}
The aim of this study is to investigate the potential of Radon Transform and Regularized Principal Component Analysis as feature extraction for classification of pedestrian, non-pedestrian and vehicles. Several classification techniques are evaluated and verified based on accuracy, specificity and computational time. Initial findings showed that the best classification technique is Naïve Bayesian along with Gaussian as kernel with 100% accuracy and execution time of 0.016s respectively for… CONTINUE READING
Highly Cited
This paper has 59 citations. REVIEW CITATIONS

7 Figures & Tables

Topics

Statistics

010203020112012201320142015201620172018
Citations per Year

60 Citations

Semantic Scholar estimates that this publication has 60 citations based on the available data.

See our FAQ for additional information.