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Showing 1 - 20 results of 55 for search '(( primary classes based optimization algorithm ) OR ( binary image wolf optimization algorithm ))', query time: 0.53s Refine Results
  1. 1
    Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm

    Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm by Hussein Ali Bardan (21976208)

    Published 2025
    “…In this work, we propose a novel framework that integrates </p><p dir="ltr">Convolutional Neural Networks (CNNs) for image classification and a binary Grey Wolf Optimization (GWO) </p><p dir="ltr">algorithm for feature selection. …”
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  2. 2
    Average ca for HT-based features extracted from 2.4-second time segments using classification methods.

    Average ca for HT-based features extracted from 2.4-second time segments using classification methods. by Ebru Ergün (21395498)

    Published 2025
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  3. 3
    Average CA for HT, FWHT, BP, and SF-based features extracted from 2.4-second time segments using the k-NN classifier.

    Average CA for HT, FWHT, BP, and SF-based features extracted from 2.4-second time segments using the k-NN classifier. by Ebru Ergün (21395498)

    Published 2025
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  4. 4
    Trainable parameters for different algorithms.

    Trainable parameters for different algorithms. by Anwar Hossain Efat (19942283)

    Published 2024
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  5. 5
    Confusion matrix for multiclass classification.

    Confusion matrix for multiclass classification. by Ebru Ergün (21395498)

    Published 2025
    “…The experimental protocol involved eight participants performing tasks across four classes of scrolling text. To optimize system accuracy and speed, EEG and NIRS data were segmented into discrete temporal windows. …”
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  6. 6
    General flow chart of the proposed method.

    General flow chart of the proposed method. by Ebru Ergün (21395498)

    Published 2025
    “…The experimental protocol involved eight participants performing tasks across four classes of scrolling text. To optimize system accuracy and speed, EEG and NIRS data were segmented into discrete temporal windows. …”
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  7. 7
    datasheet1_Graph Neural Networks for Maximum Constraint Satisfaction.pdf

    datasheet1_Graph Neural Networks for Maximum Constraint Satisfaction.pdf by Jan Tönshoff (10192709)

    Published 2021
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  8. 8
    Data_Sheet_1_Hierarchical multi-class Alzheimer’s disease diagnostic framework using imaging and clinical features.docx

    Data_Sheet_1_Hierarchical multi-class Alzheimer’s disease diagnostic framework using imaging and clinical features.docx by Yao Qin (385509)

    Published 2022
    “…The combination of selected imaging features and clinical variables improved the multi-class performance using the AdaBoost algorithm, with overall accuracy rates of 0.877 in the temporal validation set. …”
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  9. 9
    Distributions of model parameters mirror differentially expressed ion channel genes.

    Distributions of model parameters mirror differentially expressed ion channel genes. by Daniele Linaro (227790)

    Published 2022
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  10. 10
    Category range of secondary indicators.

    Category range of secondary indicators. by Yixuan Lu (9987980)

    Published 2023
    “…The pile foundation quality achieved using the optimal construction plan is classified as Class I, which prove the feasibility of the model.…”
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  11. 11
    Diagram of ANP network structure.

    Diagram of ANP network structure. by Yixuan Lu (9987980)

    Published 2023
    “…The pile foundation quality achieved using the optimal construction plan is classified as Class I, which prove the feasibility of the model.…”
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  12. 12
    Comparison of methodologies in scheme selection.

    Comparison of methodologies in scheme selection. by Yixuan Lu (9987980)

    Published 2023
    “…The pile foundation quality achieved using the optimal construction plan is classified as Class I, which prove the feasibility of the model.…”
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  13. 13
    Judgment matrix of control layer U.

    Judgment matrix of control layer U. by Yixuan Lu (9987980)

    Published 2023
    “…The pile foundation quality achieved using the optimal construction plan is classified as Class I, which prove the feasibility of the model.…”
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  14. 14
    Expert scoring flow chart.

    Expert scoring flow chart. by Yixuan Lu (9987980)

    Published 2023
    “…The pile foundation quality achieved using the optimal construction plan is classified as Class I, which prove the feasibility of the model.…”
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  15. 15
    Evaluation matrix.

    Evaluation matrix. by Yixuan Lu (9987980)

    Published 2023
    “…The pile foundation quality achieved using the optimal construction plan is classified as Class I, which prove the feasibility of the model.…”
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  16. 16
    Parameters of joint significance test.

    Parameters of joint significance test. by Yixuan Lu (9987980)

    Published 2023
    “…The pile foundation quality achieved using the optimal construction plan is classified as Class I, which prove the feasibility of the model.…”
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  17. 17
    Expert scoring values of criterion layer U<sub>1</sub>.

    Expert scoring values of criterion layer U<sub>1</sub>. by Yixuan Lu (9987980)

    Published 2023
    “…The pile foundation quality achieved using the optimal construction plan is classified as Class I, which prove the feasibility of the model.…”
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  18. 18
    Pile foundation construction options.

    Pile foundation construction options. by Yixuan Lu (9987980)

    Published 2023
    “…The pile foundation quality achieved using the optimal construction plan is classified as Class I, which prove the feasibility of the model.…”
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  19. 19
    Comparison of calculation results.

    Comparison of calculation results. by Yixuan Lu (9987980)

    Published 2023
    “…The pile foundation quality achieved using the optimal construction plan is classified as Class I, which prove the feasibility of the model.…”
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  20. 20
    Judgment matrix of criterion layer U<sub>3</sub>.

    Judgment matrix of criterion layer U<sub>3</sub>. by Yixuan Lu (9987980)

    Published 2023
    “…The pile foundation quality achieved using the optimal construction plan is classified as Class I, which prove the feasibility of the model.…”
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