An Accurate HOG based Exemplar Pyramid Method for Image Classification of Astragalus L. Taxa

According to results, the proposed exemplar pyramid generates discriminative features. because five of the used 10 classifiers achieved 100.0% classification rate.

📌 3 Key Takeaways

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Objective & Hypothesis:As known from the literature, machine learning (ML) is one of the popular researches have been used variable areas.

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Key Findings & Data:In this work, a novel exemplar pyramid method is presented to accurately classify Astragalus L. taxa by using their chromosome images.

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Conclusion & Impact:According to results, the proposed exemplar pyramid generates discriminative features. because five of the used 10 classifiers achieved 100.0% classification rate.

🔬Design:Modeling & Simulation

📍Scope:Comprehensive Sample

⚙️Variables:Chromosome · Astragalus · Image processing

Abstract

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.

Keywords

Chromosome Astragalus Image processing HOG Plant classficaiton

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Cite This Article

Emre, İ., Tuncer, T., Dogan, S., Kürşat, M., Gedik, O., Kıran, Y. (2021). An Accurate HOG based Exemplar Pyramid Method for Image Classification of Astragalus L. Taxa. Bitlis Eren University Journal of Science and Technology, Volume: 11 Issue: 2. https://doi.org/10.17678/beuscitech.948401

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