Design of Object Counting by Using Bayesian classification Algorithm
| Author(s) | : | Pranali R Sambare, Prof. Rohini Pochi |
| Institution | : | Elect & Comm Eng, T G P College |
| Published In | : | Vol. 6, Issue 5 — May 2019 |
| Page No. | : | 115-121 |
| Domain | : | Engineering |
| Type | : | Research Paper |
| ISSN (Online) | : | 2348-4470 |
| ISSN (Print) | : | 2348-6406 |
This An object counting classification scheme using Naïve Bayes Classifier is proposed in this paper. In thisNaive Bayes Classifier-based classifier of images gives as the maximum a values for decision rule. The Naïve BayesClassifier can produce very accurate classification results with a minimum training time when compared to conventionalsupervised or unsupervised learning algorithms. Comprehensive experiments for count classification tasks on an imagedataset are performed in order to evaluate the performance of the proposed classifier. The results show that theproposed Naïve Bayes Classifier outperforms conventional classifiers in terms of training speed and classificationaccuracy.
Pranali R Sambare, Prof. Rohini Pochi, “Design of Object Counting by Using Bayesian classification Algorithm”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 6, Issue 5, pp. 115-121, May 2019.
