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Showing 141 - 160 results of 389 for search '(((( algorithm setup function ) OR ( algorithm api function ))) OR ( algorithm python function ))*', query time: 0.52s Refine Results
  1. 141
    Example of use of the slightly off-axis strategies.

    Example of use of the slightly off-axis strategies. by Raul Castañeda (13932971)

    Published 2022
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  2. 142
    Example of the fully-compensated phase reconstruction package for off-axis DHM holograms recorded in telecentric configuration.

    Example of the fully-compensated phase reconstruction package for off-axis DHM holograms recorded in telecentric configuration. by Raul Castañeda (13932971)

    Published 2022
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  3. 143
    The algorithm underlying neoVM.

    The algorithm underlying neoVM. by Tanmoy Sarkar (627505)

    Published 2024
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  4. 144
    Comparison of edge detector and CHT in detecting droplets.

    Comparison of edge detector and CHT in detecting droplets. by Manibarathi Vaithiyanathan (6655274)

    Published 2019
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  5. 145
    <b>Algorithm Pseudocode</b>

    <b>Algorithm Pseudocode</b> by Yibin Zhao (22425801)

    Published 2025
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  6. 146
    Python code, input data, and outputs of Fourier analysis and Dynamic Time Warping from McGlasson et al.

    Python code, input data, and outputs of Fourier analysis and Dynamic Time Warping from McGlasson et al. by Riley McGlasson (13876874)

    Published 2024
    “…</p> <h4><strong>Python Function Files:</strong></h4> <p>radarfuncs.py: Holds three functions used for FFT and DTW analysis.…”
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  7. 147
    A Solvent Selection Framework for Porous Organic Polymers

    A Solvent Selection Framework for Porous Organic Polymers by Xue Fang (648169)

    Published 2025
    “…In this work, we present a solvent selection toolkit for functional porous organic polymers. We have developed the <i>MLoc</i> algorithm for the fast determination of Hansen solubility parameters (HSPs) for novel materials. …”
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  8. 148
    Table_1_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf

    Table_1_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

    Published 2020
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  9. 149
    Presentation_2_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf

    Presentation_2_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

    Published 2020
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  10. 150
    Table_2_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf

    Table_2_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

    Published 2020
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  11. 151
    Image_1_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf

    Image_1_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

    Published 2020
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  12. 152
    Presentation_3_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf

    Presentation_3_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

    Published 2020
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  13. 153
    Presentation_1_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf

    Presentation_1_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

    Published 2020
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  14. 154
    Table_3_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf

    Table_3_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

    Published 2020
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  15. 155
    ClaritySpectra: Raman spectra analysis tool

    ClaritySpectra: Raman spectra analysis tool by Aaron Celestian (9395696)

    Published 2025
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  16. 156
    Open Binding Pose Metadynamics: An Effective Approach for the Ranking of Protein–Ligand Binding Poses

    Open Binding Pose Metadynamics: An Effective Approach for the Ranking of Protein–Ligand Binding Poses by Dominykas Lukauskis (14143149)

    Published 2022
    “…OpenBPMD is powered by the OpenMM simulation engine and uses a revised scoring function. The algorithm was validated by testing it on a wide range of targets and showing that it matches or exceeds the performance of the original BPMD. …”
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  17. 157
    Open Binding Pose Metadynamics: An Effective Approach for the Ranking of Protein–Ligand Binding Poses

    Open Binding Pose Metadynamics: An Effective Approach for the Ranking of Protein–Ligand Binding Poses by Dominykas Lukauskis (14143149)

    Published 2022
    “…OpenBPMD is powered by the OpenMM simulation engine and uses a revised scoring function. The algorithm was validated by testing it on a wide range of targets and showing that it matches or exceeds the performance of the original BPMD. …”
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  18. 158
    Open Binding Pose Metadynamics: An Effective Approach for the Ranking of Protein–Ligand Binding Poses

    Open Binding Pose Metadynamics: An Effective Approach for the Ranking of Protein–Ligand Binding Poses by Dominykas Lukauskis (14143149)

    Published 2022
    “…OpenBPMD is powered by the OpenMM simulation engine and uses a revised scoring function. The algorithm was validated by testing it on a wide range of targets and showing that it matches or exceeds the performance of the original BPMD. …”
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  19. 159
    DataSheet1_Multi_Scale_Tools: A Python Library to Exploit Multi-Scale Whole Slide Images.PDF

    DataSheet1_Multi_Scale_Tools: A Python Library to Exploit Multi-Scale Whole Slide Images.PDF by Niccolò Marini (11247936)

    Published 2021
    “…<p>Algorithms proposed in computational pathology can allow to automatically analyze digitized tissue samples of histopathological images to help diagnosing diseases. …”
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  20. 160
    BOFdat Step 3: Identifying species-specific metabolic end goals.

    BOFdat Step 3: Identifying species-specific metabolic end goals. by Jean-Christophe Lachance (6619307)

    Published 2019
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