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crowding classification » protein classification (Expand Search), learning classification (Expand Search), crop classification (Expand Search)
common optimization » codon optimization (Expand Search), carbon optimization (Expand Search), cosmic optimization (Expand Search)
based crowding » based grading (Expand Search), based reading (Expand Search), based grouping (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
binary a » binary _ (Expand Search), binary b (Expand Search), hilary a (Expand Search)
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Showing 1 - 20 results of 27 for search '(( binary based crowding classification algorithm ) OR ( binary a common optimization algorithm ))', query time: 0.53s Refine Results
  1. 1
    Explicability results of the crowding classification model.

    Explicability results of the crowding classification model. by Kengo Oka (1420585)

    Published 2025
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  2. 2
    Association between crowding and oral habits.

    Association between crowding and oral habits. by Kengo Oka (1420585)

    Published 2025
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  3. 3
    Explicability results of the deep bite classification model.

    Explicability results of the deep bite classification model. by Kengo Oka (1420585)

    Published 2025
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  4. 4
    Explicability results of the maxillary protrusion classification model.

    Explicability results of the maxillary protrusion classification model. by Kengo Oka (1420585)

    Published 2025
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  5. 5
    Association between maxillary protrusion and oral habits.

    Association between maxillary protrusion and oral habits. by Kengo Oka (1420585)

    Published 2025
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  6. 6
    Guide frame that appears on the smartphone application.

    Guide frame that appears on the smartphone application. by Kengo Oka (1420585)

    Published 2025
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  7. 7
    Association between deep bite and oral habits.

    Association between deep bite and oral habits. by Kengo Oka (1420585)

    Published 2025
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  8. 8
    Performance metrics of the logistic regression models on the test dataset.

    Performance metrics of the logistic regression models on the test dataset. by Kengo Oka (1420585)

    Published 2025
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  9. 9
    Representative photographic image.

    Representative photographic image. by Kengo Oka (1420585)

    Published 2025
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  10. 10
    Breakdown of participants by residential area.

    Breakdown of participants by residential area. by Kengo Oka (1420585)

    Published 2025
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  11. 11
    Flowchart of study participants and design.

    Flowchart of study participants and design. by Kengo Oka (1420585)

    Published 2025
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  12. 12
    Breakdown of participants by annual household income.

    Breakdown of participants by annual household income. by Kengo Oka (1420585)

    Published 2025
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  13. 13
    Performance metrics of the machine learning models on the test dataset.

    Performance metrics of the machine learning models on the test dataset. by Kengo Oka (1420585)

    Published 2025
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  14. 14
    Each variable for the dataset.

    Each variable for the dataset. by Kengo Oka (1420585)

    Published 2025
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  15. 15
    Binary contingency table.

    Binary contingency table. by Lu Xiao (314030)

    Published 2024
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  16. 16
    Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results

    Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results by Se-Hee Jo (20554623)

    Published 2025
    “…A Python-based algorithm was developed for estimating the nonrandom two-liquid (NRTL) model parameters of aqueous binary systems in a straightforward manner from simplified molecular-input line-entry specification (SMILES) strings of substances in a system. …”
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  17. 17
    DataSheet_1_Raman Spectroscopic Differentiation of Streptococcus pneumoniae From Other Streptococci Using Laboratory Strains and Clinical Isolates.pdf

    DataSheet_1_Raman Spectroscopic Differentiation of Streptococcus pneumoniae From Other Streptococci Using Laboratory Strains and Clinical Isolates.pdf by Marcel Dahms (9160118)

    Published 2022
    “…Improvement of the classification rate is expected with optimized model parameters and algorithms as well as with a larger spectral data base for training.…”
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  18. 18
    MCLP_quantum_annealer_V0.5

    MCLP_quantum_annealer_V0.5 by Anonymous Anonymous (4854526)

    Published 2025
    “…Currently, classical high-performance and parallel spatial computing architectures are commonly employed to solve geospatial optimization problems. …”
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  19. 19
    Generalized Tensor Decomposition With Features on Multiple Modes

    Generalized Tensor Decomposition With Features on Multiple Modes by Jiaxin Hu (1327875)

    Published 2021
    “…Our proposal handles a broad range of data types, including continuous, count, and binary observations. …”
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  20. 20
    Contextual Dynamic Pricing with Strategic Buyers

    Contextual Dynamic Pricing with Strategic Buyers by Pangpang Liu (18886419)

    Published 2024
    “…This underscores the rate optimality of our policy. Importantly, our policy is not a mere amalgamation of existing dynamic pricing policies and strategic behavior handling algorithms. …”
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