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Showing 41 - 60 results of 2,677 for search '(( elements method algorithm ) OR ((( data code algorithm ) OR ( based mapping algorithm ))))*', query time: 0.47s Refine Results
  1. 41
    The fitness of NANEAT model evolution.

    The fitness of NANEAT model evolution. by Wenbing Shi (5806160)

    Published 2025
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  2. 42
    The speciation of NANEAT model evolution.

    The speciation of NANEAT model evolution. by Wenbing Shi (5806160)

    Published 2025
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  3. 43
    Data & code.

    Data & code. by Mingming Li (502877)

    Published 2024
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  4. 44
    Research data and code file

    Research data and code file by shuo zhang (21176735)

    Published 2025
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  5. 45
    Data Sheet 1_Semantic composition of robotic solver algorithms on graph structures.pdf

    Data Sheet 1_Semantic composition of robotic solver algorithms on graph structures.pdf by Sven Schneider (1366548)

    Published 2025
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  6. 46
    Optimal Channel Encoding/Decoding Algorithm Design with MATLAB

    Optimal Channel Encoding/Decoding Algorithm Design with MATLAB by Saraf Mohaimen Chowdhury (21977243)

    Published 2025
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  7. 47
    Code and data - WST 895 thesis

    Code and data - WST 895 thesis by Hoosain Ebrahim (14058588)

    Published 2025
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  8. 48
    ATF-DF-WA Algorithm Experimental Code

    ATF-DF-WA Algorithm Experimental Code by jinhao zhong (20616116)

    Published 2025
    “…<p dir="ltr">The provided code files serve the following purposes:</p><ul><li><b>Preprocess.py</b> – This script handles text preprocessing tasks, such as cleaning and preparing raw text data for further processing.…”
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  9. 49
    Calculation algorithm implementing the proposed model.

    Calculation algorithm implementing the proposed model. by Landry Djopkop Kouanang (17131748)

    Published 2025
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  10. 50
    Calculation algorithm implementing the proposed model.

    Calculation algorithm implementing the proposed model. by Landry Djopkop Kouanang (17131748)

    Published 2025
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  11. 51
    Uniform Manifold Approximation and Projection (UMAP)-based sorting enhances detection of low-firing rate neurons and boosts mutual information.

    Uniform Manifold Approximation and Projection (UMAP)-based sorting enhances detection of low-firing rate neurons and boosts mutual information. by Daniel Suárez-Barrera (22676654)

    Published 2025
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  12. 52
    QQESPM-GS - Codes and Data

    QQESPM-GS - Codes and Data by Carlos Pontes (20835533)

    Published 2025
    “…<p dir="ltr">Codes and Data for the algorithms, methods and experiments presented in the paper titled "QQESPM-GS: an Efficient Solution for Geo-textual Search Parameterized by Graph-based Spatial Patterns".…”
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  13. 53
    Mapping between textual description and Algorithm 1 components.

    Mapping between textual description and Algorithm 1 components. by Adel Alshamrani (22022154)

    Published 2025
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  14. 54
    Main code.

    Main code. by Jingguo Bi (21439766)

    Published 2025
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  15. 55
    Code and data.

    Code and data. by Crispin H. V. Cooper (21484906)

    Published 2025
    “…We suggest that the metaphor of discrete echo chambers may be inappropriate for meta-opinions: while measures of meta-opinion accuracy and its influences can reveal echo chamber characteristics where other metrics confirm their presence, the presence or absence of meta-opinion clusters is not itself sufficient to define an echo chamber. We publish both data and analysis code as supplementary material.…”
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  16. 56
    Algorithmic experimental parameter design.

    Algorithmic experimental parameter design. by Chuanxi Xing (20141665)

    Published 2024
    “…Furthermore, the estimation of the DOA can be accurately carried out under low signal-to-noise ratio conditions. This method effectively utilizes the degrees of freedom provided by the virtual array, reducing noise interference, and exhibiting better performance in terms of positioning accuracy and algorithm stability.…”
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  17. 57
    Source Code and Dataset

    Source Code and Dataset by Swathi Ganesan (14394924)

    Published 2025
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  18. 58
    Correlation matrices of handcrafted features before and after feature selection. The figure presents two heatmaps illustrating the correlation among 52 handcrafted features derived from the 3-level wavelet transform (WT) at four resolutions. These features were used as inputs for traditional ML algorithms. The left map demonstrates the correlation matrix of 52 features crafted from 4 resolutions of the 3-level WT, which are used as inputs for traditional ML algorithms. The heat map (on the right) is the correlation matrix after feature selection, in which features whose Pearson’s correlation coefficient is higher than 0.8 are considered highly correlated. We keep only one representative feature and remove its highly correlated features.

    Correlation matrices of handcrafted features before and after feature selection. The figure presents two heatmaps illustrating the correlation among 52 handcrafted features derived... by Quang Dung Dinh (20995766)

    Published 2025
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  19. 59
    Code for Most Likely Paths Calculation_ERP

    Code for Most Likely Paths Calculation_ERP by Mengqi Yang (21263402)

    Published 2025
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  20. 60
    YOLO series algorithms in the detection of infrared target city mAP value results of the map.

    YOLO series algorithms in the detection of infrared target city mAP value results of the map. by Huiying Zhang (200681)

    Published 2025
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