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Showing 161 - 180 results of 306 for search '(( elements ppm algorithm ) OR ((( implement learner algorithm ) OR ( level coding algorithm ))))', query time: 0.33s Refine Results
  1. 161
    Selection strategy process.

    Selection strategy process. by Hui Yang (91136)

    Published 2024
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  2. 162
    Division accuracy.

    Division accuracy. by Hui Yang (91136)

    Published 2024
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  3. 163
    The division of CTU in the equatorial region.

    The division of CTU in the equatorial region. by Hui Yang (91136)

    Published 2024
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  4. 164
    Adjusting the process.

    Adjusting the process. by Hui Yang (91136)

    Published 2024
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  5. 165
    Indicator analysis of integrated models.

    Indicator analysis of integrated models. by Hui Yang (91136)

    Published 2024
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  6. 166
    UC division situation.

    UC division situation. by Hui Yang (91136)

    Published 2024
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  7. 167
    Comparison of deep partitioning models.

    Comparison of deep partitioning models. by Hui Yang (91136)

    Published 2024
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  8. 168
    Projection weight distribution.

    Projection weight distribution. by Hui Yang (91136)

    Published 2024
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  9. 169
    Horizontal comparison of models.

    Horizontal comparison of models. by Hui Yang (91136)

    Published 2024
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  10. 170
    Adaptive model BD rate analysis.

    Adaptive model BD rate analysis. by Hui Yang (91136)

    Published 2024
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  11. 171
    Index analysis of deep partitioning strategy.

    Index analysis of deep partitioning strategy. by Hui Yang (91136)

    Published 2024
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  12. 172
    Example of time-frequency representation of sEMG signal.

    Example of time-frequency representation of sEMG signal. by Francesco Di Nardo (734450)

    Published 2025
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  13. 173
    <b>The abundance of ground-level atmospheric ice-nucleating particles and aerosol properties </b><b>in the North Slope of Alaska</b>

    <b>The abundance of ground-level atmospheric ice-nucleating particles and aerosol properties </b><b>in the North Slope of Alaska</b> by Aidan Pantoya (19416546)

    Published 2024
    “…It is worth noting that we also flag the data based on wind speed and number concentration, and data mentor edits. The algorithm we use is described in this paper (Sheridan et al., 2016). …”
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  14. 174
    LBQANA python code + Merged Gene Expression Dataset from GSE10810, GSE17907, GSE20711, GSE42568, GSE45827, and GSE61304 for Breast Cancer Biomarker Discovery

    LBQANA python code + Merged Gene Expression Dataset from GSE10810, GSE17907, GSE20711, GSE42568, GSE45827, and GSE61304 for Breast Cancer Biomarker Discovery by M RN (9866504)

    Published 2025
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  15. 175
    In each subplot we show in yellow the (vertical) for arm-2 as a function of the number of SNPs corresponding to each -threshold (horizontal, log-scale).

    In each subplot we show in yellow the (vertical) for arm-2 as a function of the number of SNPs corresponding to each -threshold (horizontal, log-scale). by Caroline C. McGrouther (5216153)

    Published 2025
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  16. 176
    Kleptographic Attacks Against Implicit Rejection

    Kleptographic Attacks Against Implicit Rejection by Antoine Joux (17288464)

    Published 2025
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  17. 177
    Performance comparison of different clustering strategies.

    Performance comparison of different clustering strategies. by Katharina Waury (14203284)

    Published 2025
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  18. 178
    <b>BRISC: Annotated Dataset for Brain Tumor Segmentation and Classification</b>

    <b>BRISC: Annotated Dataset for Brain Tumor Segmentation and Classification</b> by BRISC Dataset (22559540)

    Published 2025
    “…It provides high-quality, physician-validated pixel-level masks and a balanced multi-class classification split, suitable for benchmarking segmentation and classification algorithms as well as multi-task learning research.…”
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  19. 179
    Factors influencing the discovery of new genetic signatures.

    Factors influencing the discovery of new genetic signatures. by Wei Liu (20030)

    Published 2024
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  20. 180
    A. Scatter plot of the training set data before batch correction; B: Scatter plot of the training set data after batch correction.

    A. Scatter plot of the training set data before batch correction; B: Scatter plot of the training set data after batch correction. by Min-xiao Wang (20868922)

    Published 2025
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