Research Article
Teeth Category Classification by Fractional Fourier Entropy and Improved Hybrid Genetic Algorithm
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@INPROCEEDINGS{10.1007/978-3-030-51103-6_23, author={Siyuan Lu and Liam O’Donnell}, title={Teeth Category Classification by Fractional Fourier Entropy and Improved Hybrid Genetic Algorithm}, proceedings={Multimedia Technology and Enhanced Learning. Second EAI International Conference, ICMTEL 2020, Leicester, UK, April 10-11, 2020, Proceedings, Part II}, proceedings_a={ICMTEL PART 2}, year={2020}, month={7}, keywords={Teeth classification Fractional fourier transform Entropy Neural network Genetic algorithm}, doi={10.1007/978-3-030-51103-6_23} }- Siyuan Lu
Liam O’Donnell
Year: 2020
Teeth Category Classification by Fractional Fourier Entropy and Improved Hybrid Genetic Algorithm
ICMTEL PART 2
Springer
DOI: 10.1007/978-3-030-51103-6_23
Abstract
It is significant to classify teeth categories in dental treatment. A novel teeth classification method was proposed in this paper, which combined fractional Fourier entropy and feedforward neural network. Firstly, fractional Fourier transform was performed on the teeth CT images and the obtained spectrums were used to extract entropies as the features. Then, a feedforward neural network was employed for automatic classification. To train the parameters in the network, improved hybrid genetic algorithm was leveraged. Experiment results suggested that our method achieved state-of-the-art performance.
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