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Showing 1 - 20 results of 624 for search '(( element te algorithm ) OR ((( text using algorithm ) OR ( neural coding algorithm ))))', query time: 0.36s Refine Results
  1. 1
    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
    “…The data is stored in JSON format under the following labels:</p><ul><li><b>"kannada text"</b> – Kannada algorithmic statement</li><li><b>"text"</b> – English algorithmic statement</li><li><b>"code"</b> – Expected Python output</li></ul><h4><b>Dataset Highlights: -</b></h4><ul><li><b>Triplet Structure:</b> Kannada algorithmic statements, their English translations, and Python code.…”
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  2. 2
    The optimal combination of text representations and classifiers for different-size text sets.

    The optimal combination of text representations and classifiers for different-size text sets. by Lu Xiao (314030)

    Published 2024
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  3. 3
    Data and code resources.

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

    Published 2025
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  4. 4
    Abbreviations used in the text.

    Abbreviations used in the text. by Lorenzo Ruinelli (13014138)

    Published 2025
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  5. 5
    Flowchart of the framework of text classification algorithm for subordinate classes of tourist attractions.

    Flowchart of the framework of text classification algorithm for subordinate classes of tourist attractions. by Lu Xiao (314030)

    Published 2024
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  6. 6
    The visual screen displaying the scrolling text used during the experiment.

    The visual screen displaying the scrolling text used during the experiment. by Ebru Ergün (21395498)

    Published 2025
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  7. 7
    TIR-Learner v3: New generation TE annotation program for identifying TIRs

    TIR-Learner v3: New generation TE annotation program for identifying TIRs by Tianyu Lu (18856792)

    Published 2025
    “…The old TIR suffers from slow execution on large genomes due to intense I/O operations and less efficient algorithms, it also lacks maintainability due to legacy dependency issues. …”
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  8. 8
    Recall results of four algorithms.

    Recall results of four algorithms. by Nan Xu (107466)

    Published 2024
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  9. 9
    Tourist attraction description text data.

    Tourist attraction description text data. by Lu Xiao (314030)

    Published 2024
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  10. 10
    Frequency of occurrence of different text lengths.

    Frequency of occurrence of different text lengths. by Lu Xiao (314030)

    Published 2024
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  11. 11
    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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  12. 12
    Precision and recall results of three algorithms.

    Precision and recall results of three algorithms. by Nan Xu (107466)

    Published 2024
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  13. 13
    Evaluation index results of five algorithms.

    Evaluation index results of five algorithms. by Nan Xu (107466)

    Published 2024
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  14. 14
    Schematic diagram of DD algorithm flow.

    Schematic diagram of DD algorithm flow. by Nan Xu (107466)

    Published 2024
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  15. 15
    The genome coding scheme.

    The genome coding scheme. by Wenbing Shi (5806160)

    Published 2025
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  16. 16
    Performances of text augmentation approaches.

    Performances of text augmentation approaches. by Rodrigo Gutiérrez Benítez (19746443)

    Published 2024
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  17. 17
    Word segmentation speed results of four algorithms.

    Word segmentation speed results of four algorithms. by Nan Xu (107466)

    Published 2024
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  18. 18
    Influence of hyperparameters on experimental results in IST algorithm.

    Influence of hyperparameters on experimental results in IST algorithm. by Ke Zhang (115386)

    Published 2024
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  19. 19
    The optimal number of clusters identified using the GMM clustering algorithm.

    The optimal number of clusters identified using the GMM clustering algorithm. by Dinh K. Tang (20469082)

    Published 2024
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  20. 20
    Optimal number of clusters identified using the GMM clustering algorithm.

    Optimal number of clusters identified using the GMM clustering algorithm. by Dinh K. Tang (20469082)

    Published 2024
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