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Showing 1 - 20 results of 846 for search '(((( element g algorithm ) OR ( complete detection algorithm ))) OR ( neural coding algorithm ))', query time: 0.35s Refine Results
  1. 1
    GA pseudo-code.

    GA pseudo-code. by Jianpeng Zhang (528185)

    Published 2025
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  2. 2
    Pseudo-code for the study design model.

    Pseudo-code for the study design model. by Jianpeng Zhang (528185)

    Published 2025
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  3. 3
    EFGs: A Complete and Accurate Implementation of Ertl’s Functional Group Detection Algorithm in RDKit

    EFGs: A Complete and Accurate Implementation of Ertl’s Functional Group Detection Algorithm in RDKit by Gonzalo Colmenarejo (650249)

    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
    Summary of four signal detection algorithms.

    Summary of four signal detection algorithms. by Wangyu Ye (17616256)

    Published 2025
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  6. 6
    Data and code resources.

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

    Published 2025
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  7. 7
    Flow of complete face detection method.

    Flow of complete face detection method. by Yingying Mei (13817440)

    Published 2025
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  8. 8
    Schematic diagram of elements in the delivery area.

    Schematic diagram of elements in the delivery area. by Yingbo Mao (22522192)

    Published 2025
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  9. 9
    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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  10. 10
    The genome coding scheme.

    The genome coding scheme. by Wenbing Shi (5806160)

    Published 2025
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  11. 11
    Target detection results (the detection results of proposed algorithm are on the left and YOLOv7 is on the middle YOLOv8-n is on the right).

    Target detection results (the detection results of proposed algorithm are on the left and YOLOv7 is on the middle YOLOv8-n is on the right). by Xiangqian Xu (17310895)

    Published 2024
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  12. 12
    Comparison chart of the ablation test detection.

    Comparison chart of the ablation test detection. by Wenyuan Xu (2553028)

    Published 2025
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  13. 13
    Comparison of the detection effect of different models.

    Comparison of the detection effect of different models. by Wenyuan Xu (2553028)

    Published 2025
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  14. 14
    A comparison chart of the detection effect.

    A comparison chart of the detection effect. by Wenyuan Xu (2553028)

    Published 2025
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  15. 15
    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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  16. 16
    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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  17. 17
    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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  18. 18
    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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  19. 19
    Performance comparison results of different algorithms.

    Performance comparison results of different algorithms. by Wenyuan Xu (2553028)

    Published 2025
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  20. 20
    Target detection results in different scenes (the detection results of proposed algorithm are on the left and YOLOv7 is on the middle YOLOv8-n is on the right).

    Target detection results in different scenes (the detection results of proposed algorithm are on the left and YOLOv7 is on the middle YOLOv8-n is on the right). by Xiangqian Xu (17310895)

    Published 2024
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