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Showing 21 - 38 results of 38 for search '(("different clustering algorithm") OR ("element mesh algorithm"))', query time: 0.28s Refine Results
  1. 21
    Clusterings’ visualization obtained by t-SNE from the <i>D</i><sub>4</sub> dataset, considering the best pair TAMURA_ROCK (descriptor_clustering algorithm), and according to the DAVIES metric.

    Clusterings’ visualization obtained by t-SNE from the <i>D</i><sub>4</sub> dataset, considering the best pair TAMURA_ROCK (descriptor_clustering algorithm), and according to the DA... by Eduardo R. de Oliveira (16883983)

    Published 2023
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  2. 22
    Clustering methods used in our experiments.

    Clustering methods used in our experiments. by Eduardo R. de Oliveira (16883983)

    Published 2023
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  3. 23
    Clusterings’ visualization obtained by PCA from the <i>D</i><sub>4</sub> dataset, considering the best pair MPO_ROCK (descriptor_clustering algorithm), and according to the CALINSKI metric.

    Clusterings’ visualization obtained by PCA from the <i>D</i><sub>4</sub> dataset, considering the best pair MPO_ROCK (descriptor_clustering algorithm), and according to the CALINSK... by Eduardo R. de Oliveira (16883983)

    Published 2023
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  4. 24
    Classes’ descriptions, samples’ distribution for each class of dataset <i>D</i><sub>1</sub>, and their respective severity levels.

    Classes’ descriptions, samples’ distribution for each class of dataset <i>D</i><sub>1</sub>, and their respective severity levels. by Eduardo R. de Oliveira (16883983)

    Published 2023
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  5. 25
    Pipeline of our proposed methodology.

    Pipeline of our proposed methodology. by Eduardo R. de Oliveira (16883983)

    Published 2023
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  6. 26
    Classes’ descriptions and samples’ distribution for each class of dataset <i>D</i><sub>5</sub>.

    Classes’ descriptions and samples’ distribution for each class of dataset <i>D</i><sub>5</sub>. by Eduardo R. de Oliveira (16883983)

    Published 2023
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  7. 27
    Classes’ descriptions, samples’ distribution for each class of dataset <i>D</i><sub>3</sub>, and their respective severity levels.

    Classes’ descriptions, samples’ distribution for each class of dataset <i>D</i><sub>3</sub>, and their respective severity levels. by Eduardo R. de Oliveira (16883983)

    Published 2023
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  8. 28
    Classes’ descriptions, samples’ distribution for each class of dataset <i>D</i><sub>2</sub>, and their respective severity levels.

    Classes’ descriptions, samples’ distribution for each class of dataset <i>D</i><sub>2</sub>, and their respective severity levels. by Eduardo R. de Oliveira (16883983)

    Published 2023
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  9. 29
    Accuracy results obtained by each descriptor and clustering method from the dataset <i>D</i><sub>2</sub>.

    Accuracy results obtained by each descriptor and clustering method from the dataset <i>D</i><sub>2</sub>. by Eduardo R. de Oliveira (16883983)

    Published 2023
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  10. 30
    Results obtained by each descriptor and clustering method ROCK, considering each of the metrics (accuracy, FOWLKES, DAVIES and CALINSKI), from the dataset <i>D</i><sub>5</sub>.

    Results obtained by each descriptor and clustering method ROCK, considering each of the metrics (accuracy, FOWLKES, DAVIES and CALINSKI), from the dataset <i>D</i><sub>5</sub>. by Eduardo R. de Oliveira (16883983)

    Published 2023
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  11. 31
    Results obtained by each descriptor and clustering method CURE, considering each of the metrics (accuracy, FOWLKES, DAVIES and CALINSKI), from the dataset <i>D</i><sub>1</sub>.

    Results obtained by each descriptor and clustering method CURE, considering each of the metrics (accuracy, FOWLKES, DAVIES and CALINSKI), from the dataset <i>D</i><sub>1</sub>. by Eduardo R. de Oliveira (16883983)

    Published 2023
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  12. 32
    Accuracy results obtained by each descriptor and clustering method from the dataset <i>D</i><sub>5</sub>.

    Accuracy results obtained by each descriptor and clustering method from the dataset <i>D</i><sub>5</sub>. by Eduardo R. de Oliveira (16883983)

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  13. 33
    Matrix reorganization to reach the best accuracy from a given cluster: (a) before and (b) after reorganization.

    Matrix reorganization to reach the best accuracy from a given cluster: (a) before and (b) after reorganization. by Eduardo R. de Oliveira (16883983)

    Published 2023
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  14. 34
    Results obtained by each descriptor and clustering method ROCK, considering each of the metrics (accuracy, FOWLKES, DAVIES and CALINSKI), from the dataset <i>D</i><sub>3</sub>.

    Results obtained by each descriptor and clustering method ROCK, considering each of the metrics (accuracy, FOWLKES, DAVIES and CALINSKI), from the dataset <i>D</i><sub>3</sub>. by Eduardo R. de Oliveira (16883983)

    Published 2023
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  15. 35
    Clusterings’ visualization obtained by t-SNE from the <i>D</i><sub>4</sub> dataset, considering the best pair RCS_ROCK (descriptor_clustering algorithm), and according to the accuracy metric.

    Clusterings’ visualization obtained by t-SNE from the <i>D</i><sub>4</sub> dataset, considering the best pair RCS_ROCK (descriptor_clustering algorithm), and according to the accur... by Eduardo R. de Oliveira (16883983)

    Published 2023
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  16. 36
    Image descriptors used to extract features from each soybean seed image, and their respective feature vector dimensionality.

    Image descriptors used to extract features from each soybean seed image, and their respective feature vector dimensionality. by Eduardo R. de Oliveira (16883983)

    Published 2023
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  17. 37
    Number of classes and samples for each dataset.

    Number of classes and samples for each dataset. by Eduardo R. de Oliveira (16883983)

    Published 2023
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  18. 38
    Accuracy results obtained by each descriptor and clustering method from the dataset <i>D</i><sub>4</sub>.

    Accuracy results obtained by each descriptor and clustering method from the dataset <i>D</i><sub>4</sub>. by Eduardo R. de Oliveira (16883983)

    Published 2023
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