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Showing 1 - 20 results of 72 for search '(( library based search optimization algorithm ) OR ( binary cases based optimization algorithm ))', query time: 0.58s Refine Results
  1. 1
    Comparison between ILSTM and machine learning-based algorithms in binary classification.

    Comparison between ILSTM and machine learning-based algorithms in binary classification. by Asmaa Ahmed Awad (16726315)

    Published 2023
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  2. 2
    Comparison between ILSTM and deep learning-based algorithms in binary classification.

    Comparison between ILSTM and deep learning-based algorithms in binary classification. by Asmaa Ahmed Awad (16726315)

    Published 2023
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  3. 3
    MSE for ILSTM algorithm in binary classification.

    MSE for ILSTM algorithm in binary classification. by Asmaa Ahmed Awad (16726315)

    Published 2023
    “…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …”
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  4. 4
    Several loop patterns found in binary code.

    Several loop patterns found in binary code. by Alba Pedro-Zapater (8600382)

    Published 2020
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  5. 5
    Train test validation libraries.

    Train test validation libraries. by Muhammad Usman Tariq (11022141)

    Published 2021
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  6. 6
    ReaLigands: A Ligand Library Cultivated from Experiment and Intended for Molecular Computational Catalyst Design

    ReaLigands: A Ligand Library Cultivated from Experiment and Intended for Molecular Computational Catalyst Design by Shu-Sen Chen (1777108)

    Published 2023
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  7. 7
    SSA4LSMOP

    SSA4LSMOP by Zongbin Qiao (19814199)

    Published 2024
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  8. 8
    Closed search (±5ppm) comparison against Crux and MSFragger using real-world data from PRIDE repository PXD000612 (top), PXD009861 (middle), and PXD001468 (bottom).

    Closed search (±5ppm) comparison against Crux and MSFragger using real-world data from PRIDE repository PXD000612 (top), PXD009861 (middle), and PXD001468 (bottom). by Muhammad Usman Tariq (11022141)

    Published 2021
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  9. 9
    Training parameters for SpeCollate.

    Training parameters for SpeCollate. by Muhammad Usman Tariq (11022141)

    Published 2021
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  10. 10
    Peptides.

    Peptides. by Muhammad Usman Tariq (11022141)

    Published 2021
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  11. 11
    Fig 9 -

    Fig 9 - by Muhammad Usman Tariq (11022141)

    Published 2021
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  12. 12
    UMAP.

    UMAP. by Muhammad Usman Tariq (11022141)

    Published 2021
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  13. 13
    Process of generating MS/MS spectra from a protein mixture using mass-spectrometry analysis.

    Process of generating MS/MS spectra from a protein mixture using mass-spectrometry analysis. by Muhammad Usman Tariq (11022141)

    Published 2021
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  14. 14
    Modifications and the character values used in the training data.

    Modifications and the character values used in the training data. by Muhammad Usman Tariq (11022141)

    Published 2021
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  15. 15
    2D UMAP visualization of embedded spectra and peptide vectors generated by SpeCollate.

    2D UMAP visualization of embedded spectra and peptide vectors generated by SpeCollate. by Muhammad Usman Tariq (11022141)

    Published 2021
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  16. 16
    Fig 6 -

    Fig 6 - by Muhammad Usman Tariq (11022141)

    Published 2021
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  17. 17
    Online sextuplet mining for SNAP-loss.

    Online sextuplet mining for SNAP-loss. by Muhammad Usman Tariq (11022141)

    Published 2021
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  18. 18
    SpeCollate: Deep Similarity Network for proteomics.

    SpeCollate: Deep Similarity Network for proteomics. by Muhammad Usman Tariq (11022141)

    Published 2021
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  19. 19
    A generic proteomics flow.

    A generic proteomics flow. by Muhammad Usman Tariq (11022141)

    Published 2021
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  20. 20
    Space transition methods.

    Space transition methods. by Muhammad Usman Tariq (11022141)

    Published 2021
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