Vehicle image classification using data mining techniques
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Date
2019-05-24
Journal Title
Journal ISSN
Volume Title
Publisher
Association for Computing Machinery
Abstract
This paper focuses on the application of different data mining techniques to classify images of vehicles into three classes using Weka. The dataset used for this study were collected from Google Image search engine and other dataset websites. In preprocessing the images, filters such as Color Layout, Edge Histogram and Pyramid Histogram of Oriented Gradients were explored to extract the image features from the dataset. Classification techniques such as Multilayer Perceptron, Sequential Minimal Optimization, Logistic Model Trees, Simple Logistic and Random Forest were used. Results of the study showed that the edge histogram features provided much information to the classifiers in order to correctly classify the images. The SMO classifier performs best with the highest accuracy of 82.37%.
Description
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Keywords
Machine learning, Pattern recognition
Citation
Suguitan, A. S. & Dacaymat, L. N. (2019). Vehicle image classification using data mining techniques. ACM International Conference Proceeding Series, 13 - 17. https://10.1145/3339363.3339366
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