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Showing 1 - 20 results of 268 for search '(((( complement c5 algorithm ) OR ( alignment network algorithm ))) OR ( neural coding algorithm ))', query time: 0.47s Refine Results
  1. 1
    Comparison of optical and silicon-based neural network implementations.

    Comparison of optical and silicon-based neural network implementations. by Reyhane Ahmadi (14857363)

    Published 2024
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  2. 2
    Heuristic approaches for configuring network alignment algorithms.

    Heuristic approaches for configuring network alignment algorithms. by Giuseppe Agapito (104634)

    Published 2025
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  3. 3
    Comparison of power consumption in optical and silicon-based neural network implementations.

    Comparison of power consumption in optical and silicon-based neural network implementations. by Reyhane Ahmadi (14857363)

    Published 2024
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  4. 4
    Accuracy of different electrical and optical neural networks for various input noise levels.

    Accuracy of different electrical and optical neural networks for various input noise levels. by Reyhane Ahmadi (14857363)

    Published 2024
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  5. 5
    Accuracy of different electrical and optical neural network on Caltech and ETH-80 data sets.

    Accuracy of different electrical and optical neural network on Caltech and ETH-80 data sets. by Reyhane Ahmadi (14857363)

    Published 2024
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  6. 6
    Comparison of grayscale conversion algorithms.

    Comparison of grayscale conversion algorithms. by Tianke Fang (22648035)

    Published 2025
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  7. 7
    Comparison of noise reduction algorithms.

    Comparison of noise reduction algorithms. by Tianke Fang (22648035)

    Published 2025
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  8. 8
    Comparison of preprocessing methods for network alignment.

    Comparison of preprocessing methods for network alignment. by Giuseppe Agapito (104634)

    Published 2025
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  9. 9
    Key aspects of network alignment documentation.

    Key aspects of network alignment documentation. by Giuseppe Agapito (104634)

    Published 2025
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  10. 10
    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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  11. 11
    Comparison of local and global network alignment approaches.

    Comparison of local and global network alignment approaches. by Giuseppe Agapito (104634)

    Published 2025
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  12. 12
    Representative tools using heuristic strategies for network alignment.

    Representative tools using heuristic strategies for network alignment. by Giuseppe Agapito (104634)

    Published 2025
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  13. 13
    Data and code resources.

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

    Published 2025
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  14. 14
    Comparison of network representation formats.

    Comparison of network representation formats. by Giuseppe Agapito (104634)

    Published 2025
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  15. 15
    Network topologies and suitable representation formats.

    Network topologies and suitable representation formats. by Giuseppe Agapito (104634)

    Published 2025
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  16. 16
    Recommended network representation formats for different types of biological networks. Each biological network type exhibits unique topological characteristics that make certain representation formats more efficient for storage, analysis, or alignment.

    Recommended network representation formats for different types of biological networks. Each biological network type exhibits unique topological characteristics that make certain re... by Giuseppe Agapito (104634)

    Published 2025
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  17. 17
    Flowchart of the algorithm.

    Flowchart of the algorithm. by Xingan Fu (21594713)

    Published 2025
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  18. 18
    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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  19. 19
    The genome coding scheme.

    The genome coding scheme. by Wenbing Shi (5806160)

    Published 2025
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  20. 20
    UpSet diagram illustrating the overlap of DNBs selected by our method and top-ranked genes by the 13 baseline centrality-based ranking algorithms.

    UpSet diagram illustrating the overlap of DNBs selected by our method and top-ranked genes by the 13 baseline centrality-based ranking algorithms. by Fatemeh Keikha (20917848)

    Published 2025
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