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Showing 141 - 160 results of 613 for search '(((( algorithm seu function ) OR ( algorithm pre function ))) OR ( algorithm python function ))', query time: 0.67s Refine Results
  1. 141
    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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  2. 142
    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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  3. 143
    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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  4. 144
    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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  5. 145
    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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  6. 146
    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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  7. 147
    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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  8. 148
    Characterization of the TD<sup>2</sup> dataset.

    Characterization of the TD<sup>2</sup> dataset. by Benjamin Gallois (10131683)

    Published 2021
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  9. 149
    Optimization of tracking parameters based on <i>P</i><sub><i>swap</i></sub>.

    Optimization of tracking parameters based on <i>P</i><sub><i>swap</i></sub>. by Benjamin Gallois (10131683)

    Published 2021
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  10. 150
    Effect of confinment on <i>p</i><sub><i>inc</i></sub>.

    Effect of confinment on <i>p</i><sub><i>inc</i></sub>. by Benjamin Gallois (10131683)

    Published 2021
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  11. 151
    Automatic tracking parameters.

    Automatic tracking parameters. by Benjamin Gallois (10131683)

    Published 2021
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  12. 152
    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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  13. 153
    Application of the algorithm to unseen data. Presynaptic neurons labelled by rabies viral injection into layer 2/3 primary visual cortex in Penk-Cre mice.

    Application of the algorithm to unseen data. Presynaptic neurons labelled by rabies viral injection into layer 2/3 primary visual cortex in Penk-Cre mice. by Adam L. Tyson (10892822)

    Published 2021
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  14. 154
    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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  15. 155
    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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  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
    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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  18. 158
    Membership function of error E1 for tank 1.

    Membership function of error E1 for tank 1. by Tamiru Demelash Kassie (20678515)

    Published 2025
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  19. 159
    Membership function of error E2 for tank 2.

    Membership function of error E2 for tank 2. by Tamiru Demelash Kassie (20678515)

    Published 2025
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  20. 160
    Data_Sheet_1_Processing Pipeline for Atlas-Based Imaging Data Analysis of Structural and Functional Mouse Brain MRI (AIDAmri).docx

    Data_Sheet_1_Processing Pipeline for Atlas-Based Imaging Data Analysis of Structural and Functional Mouse Brain MRI (AIDAmri).docx by Niklas Pallast (6796196)

    Published 2019
    “…Following a modular structure developed in Python scripting language, the pipeline integrates established and newly developed algorithms. …”
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