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Showing 1 - 20 results of 619 for search '(((( experiments making algorithm ) OR ( elements seu algorithm ))) OR ( neural coding algorithm ))', query time: 0.43s Refine Results
  1. 1
    Top-rated mode of transport based on the SEU algorithm (SEU scores from 0 to 40).

    Top-rated mode of transport based on the SEU algorithm (SEU scores from 0 to 40). by Johannes Weyer (13392175)

    Published 2025
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  2. 2
    Comparison of grayscale conversion algorithms.

    Comparison of grayscale conversion algorithms. by Tianke Fang (22648035)

    Published 2025
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  3. 3
    Comparison of noise reduction algorithms.

    Comparison of noise reduction algorithms. by Tianke Fang (22648035)

    Published 2025
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  4. 4
    Dataset for Fine-Tuning Code Generation Models: Kannada-English Algorithmic Statements and Python Code

    Dataset for Fine-Tuning Code Generation Models: Kannada-English Algorithmic Statements and Python Code by Goutami Sooda (20714729)

    Published 2025
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  5. 5
    Data and code resources.

    Data and code resources. by Sam Hall-McMaster (10343795)

    Published 2025
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  6. 6
    The parameter setting of the evolutionary neural network.

    The parameter setting of the evolutionary neural network. by Wenbing Shi (5806160)

    Published 2025
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  7. 7
    The genome coding scheme.

    The genome coding scheme. by Wenbing Shi (5806160)

    Published 2025
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  8. 8
    Comparison of Uniform Manifold Approximation and Projection (UMAP)-based and feature-based spike sorting on synthetic data.

    Comparison of Uniform Manifold Approximation and Projection (UMAP)-based and feature-based spike sorting on synthetic data. by Daniel Suárez-Barrera (22676654)

    Published 2025
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  9. 9
    Schematic diagram of chromosome coding.

    Schematic diagram of chromosome coding. by Meilin Zhu (688698)

    Published 2025
    “…Finally, the correctness of the model is analyzed through numerical experiments, and the effectiveness of the proposed algorithm, the joint distribution strategy, and the disruption event processing idea of combining immediate processing and scheduled batch processing is analyzed. …”
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  10. 10
    The optimal number of clusters identified using the GMM clustering algorithm.

    The optimal number of clusters identified using the GMM clustering algorithm. by Dinh K. Tang (20469082)

    Published 2024
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  11. 11
    Optimal number of clusters identified using the GMM clustering algorithm.

    Optimal number of clusters identified using the GMM clustering algorithm. by Dinh K. Tang (20469082)

    Published 2024
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  12. 12
    Algorithms runtime comparison.

    Algorithms runtime comparison. by Meilin Zhu (688698)

    Published 2025
    “…Finally, the correctness of the model is analyzed through numerical experiments, and the effectiveness of the proposed algorithm, the joint distribution strategy, and the disruption event processing idea of combining immediate processing and scheduled batch processing is analyzed. …”
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  13. 13
    Impact of multiunit merging on neural information encoding.

    Impact of multiunit merging on neural information encoding. by Daniel Suárez-Barrera (22676654)

    Published 2025
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  14. 14
    Codes for "<b>A coherent power-load optimization algorithm for wind-farm-level yaw control considering wake effects via deep neural network</b>"

    Codes for "<b>A coherent power-load optimization algorithm for wind-farm-level yaw control considering wake effects via deep neural network</b>" by Yize Wang (19535173)

    Published 2024
    “…<p dir="ltr">Codes for "<b>A coherent power-load optimization algorithm for wind-farm-level yaw control considering wake effects via deep neural network</b>"</p>…”
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  15. 15
    Efficiency of different consensus algorithms.

    Efficiency of different consensus algorithms. by Jian Yun (19703997)

    Published 2024
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  16. 16
    code_4

    code_4 by Olga Ovtsarenko (20432033)

    Published 2024
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  17. 17
    Solution results of different algorithms.

    Solution results of different algorithms. by Meilin Zhu (688698)

    Published 2025
    “…Finally, the correctness of the model is analyzed through numerical experiments, and the effectiveness of the proposed algorithm, the joint distribution strategy, and the disruption event processing idea of combining immediate processing and scheduled batch processing is analyzed. …”
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  18. 18
    The genetic algorithm.

    The genetic algorithm. by Viktoria Zemliak (19500335)

    Published 2025
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  19. 19
    USDA-ARS Tucson, Arizona 2014-2022 Data Reservoir of Field Experiments with Managed Honey Bee Colonies: Annotated Hive Frame Photos: Dataset I

    USDA-ARS Tucson, Arizona 2014-2022 Data Reservoir of Field Experiments with Managed Honey Bee Colonies: Annotated Hive Frame Photos: Dataset I by Vladimir Kulyukin (21983990)

    Published 2025
    “…Our project explores and exploits this reservoir and makes public its curated subsets. This dataset is the first such subset we curated in 2024-25 under USDA-NIFA Award 205732 "DSFAS - Exploration and Exploitation of the 2014-2022 USDA-ARS Tucson, AZ Digital Data Reservoir of Field Experiments with Managed Honey Bee Colonies."…”
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  20. 20
    Experiment 5: Clustering networks that are only partially clusterable.

    Experiment 5: Clustering networks that are only partially clusterable. by Yasamin Tabatabaee (18095491)

    Published 2025
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