An Accurate HOG based Exemplar Pyramid Method for Image Classification of Astragalus L. Taxa
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Date
2021Author
EMRE, İrfan
TUNCER, Turker
DOGAN, Sengul
KÜRŞAT, Murat
GEDIK, Osman
KIRAN, Yaşar
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As known from the literature, machine learning (ML) is one of the popular researches have been used
variable areas. In this work, a novel exemplar pyramid method is presented to accurately classify
Astragalus L. taxa by using their chromosome images. To implement ML to biological images, the
proposed exemplar pyramid method is used. Histogram of Oriented Gradients (HOG) is utilized as feature
generator. The proposed exemplar pyramid method consists of preprocessing, feature generation and
concatenation, feature selection and classification phase. 10 classifiers are chosen to train and test the
extracted features. According to results, the proposed exemplar pyramid generates discriminative features.
because five of the used 10 classifiers achieved 100.0% classification rate.
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