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process classification » protein classification (Expand Search), proposed classification (Expand Search), forest classification (Expand Search)
b optimization » _ optimization (Expand Search), bboa optimization (Expand Search), fox optimization (Expand Search)
based process » based processes (Expand Search), based probes (Expand Search), based proteins (Expand Search)
lines based » lens based (Expand Search), genes based (Expand Search), lines used (Expand Search)
Showing 1 - 20 results of 88 for search '(( lines based process classification algorithm ) OR ( binary image b optimization algorithm ))', query time: 0.68s Refine Results
  1. 1
    Example of subsampling process.

    Example of subsampling process. by Sofia P. Miranda (11418930)

    Published 2021
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  2. 2
    Random forest classification method process.

    Random forest classification method process. by Yawen Zhong (2342206)

    Published 2023
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  3. 3
    Effects of the augmentation algorithm on cell-based data.

    Effects of the augmentation algorithm on cell-based data. by Philipp Fey (14660139)

    Published 2023
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  4. 4
    All augmented cell line data that was generated for this manuscript (part 4).

    All augmented cell line data that was generated for this manuscript (part 4). by Philipp Fey (14660139)

    Published 2023
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  5. 5
    All augmented cell line data that was generated for this manuscript (part 7).

    All augmented cell line data that was generated for this manuscript (part 7). by Philipp Fey (14660139)

    Published 2023
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  6. 6
    All augmented cell line data that was generated for this manuscript (part 5).

    All augmented cell line data that was generated for this manuscript (part 5). by Philipp Fey (14660139)

    Published 2023
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  7. 7
    All augmented cell line data that was generated for this manuscript (part 1).

    All augmented cell line data that was generated for this manuscript (part 1). by Philipp Fey (14660139)

    Published 2023
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  8. 8
    All augmented cell line data that was generated for this manuscript (part 2).

    All augmented cell line data that was generated for this manuscript (part 2). by Philipp Fey (14660139)

    Published 2023
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  9. 9
    All augmented cell line data that was generated for this manuscript (part 6).

    All augmented cell line data that was generated for this manuscript (part 6). by Philipp Fey (14660139)

    Published 2023
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  10. 10
    All augmented cell line data that was generated for this manuscript (part 3).

    All augmented cell line data that was generated for this manuscript (part 3). by Philipp Fey (14660139)

    Published 2023
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  11. 11
    Process of calculating the wear probability ().

    Process of calculating the wear probability (). by Natsumi Nishiyama (19928990)

    Published 2024
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  12. 12
    Inspection of Line Defects in Transition Metal Dichalcogenides Using a Microscopic Hyperspectral Imaging Technique

    Inspection of Line Defects in Transition Metal Dichalcogenides Using a Microscopic Hyperspectral Imaging Technique by Xiangmin Hu (1612399)

    Published 2022
    “…A light selection method was proposed to optimize the optical contrast of line defects. Via application of an image processing algorithm, an automatic detection of the line defects with a classification accuracy of 95% was achieved for WS<sub>2</sub>, MoS<sub>2</sub>, and MoSe<sub>2</sub>. …”
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  13. 13
    The ROC curve for the classification of normal and abnormal images by mean Amb-I of each layer of the retina, classified by AUC = 0.92.

    The ROC curve for the classification of normal and abnormal images by mean Amb-I of each layer of the retina, classified by AUC = 0.92. by Hideki Shiihara (10803160)

    Published 2023
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  14. 14
    Dataset 1: Zip file containing the figures of the presented methods and results in jpeg files

    Dataset 1: Zip file containing the figures of the presented methods and results in jpeg files by Suchismita Behera (22027316)

    Published 2025
    “…<p dir="ltr">Figures represented here illustrates the <b>metaheuristic-based band selection framework</b> for hyperspectral image classification using <b>Binary Jaya Algorithm enhanced with a mutation operator</b> to improve population diversity and avoid premature convergence. …”
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  15. 15
    Overview of the segmentation algorithm.

    Overview of the segmentation algorithm. by Michael C. Robitaille (11949174)

    Published 2022
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  16. 16
    Comparison of effect size (OR) between our GWAS with NLP-enriched phenotyping and previous GWAS with ICD-based phenotyping from Maguire et al.

    Comparison of effect size (OR) between our GWAS with NLP-enriched phenotyping and previous GWAS with ICD-based phenotyping from Maguire et al. by Yoonjung Yoonie Joo (14296640)

    Published 2023
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  17. 17
    Test-set Kappa for CNN with and without optimization.

    Test-set Kappa for CNN with and without optimization. by Javier León (162217)

    Published 2020
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  18. 18
    Test-set Kappa for RNN with and without optimization.

    Test-set Kappa for RNN with and without optimization. by Javier León (162217)

    Published 2020
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  19. 19
    Test-set Kappa for FFNN with and without optimization.

    Test-set Kappa for FFNN with and without optimization. by Javier León (162217)

    Published 2020
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  20. 20
    Test-set Kappa for RNN with and without optimization.

    Test-set Kappa for RNN with and without optimization. by Javier León (162217)

    Published 2020
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