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Showing 1 - 9 results of 9 for search '(( binary sample processing optimization algorithm ) OR ( binary a model optimization algorithm ))~', query time: 0.66s Refine Results
  1. 1
    <i>hi</i>PRS algorithm process flow.

    <i>hi</i>PRS algorithm process flow. by Michela C. Massi (14599915)

    Published 2023
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  2. 2
    Hierarchical clustering to infer a binary tree with <i>K</i> = 4 sampled populations.

    Hierarchical clustering to infer a binary tree with <i>K</i> = 4 sampled populations. by Tristan Mary-Huard (3864)

    Published 2023
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  3. 3
    Application of ABC SMC to the fitting of the binary flip with cusp model.

    Application of ABC SMC to the fitting of the binary flip with cusp model. by Elena Camacho-Aguilar (10906327)

    Published 2021
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  4. 4
    Bayesian Spatial Binary Regression for Label Fusion in Structural Neuroimaging

    Bayesian Spatial Binary Regression for Label Fusion in Structural Neuroimaging by D. Andrew Brown (6584837)

    Published 2021
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  5. 5
    MCLP_quantum_annealer_V0.5

    MCLP_quantum_annealer_V0.5 by Anonymous Anonymous (4854526)

    Published 2025
    “…This paper presents a quantum computing path for Transformation-to-Sampling-to-Verification of geospatial optimization problems, adaptable to the controlled qubit scale and coherence constraints under current NISQ conditions. …”
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  6. 6
    Thesis-RAMIS-Figs_Slides

    Thesis-RAMIS-Figs_Slides by Felipe Santibañez-Leal (10967991)

    Published 2024
    “…<br><br>Finally, although the developed concepts, ideas and algorithms have been developed for inverse problems in geostatistics, the results are applicable to a wide range of disciplines where similar sampling problems need to be faced, included but not limited to design of communication networks, optimal integration and communication of swarms of robots and drones, remote sensing.…”
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  7. 7
    Processed dataset to train and test the WGAN-GP_IMOA_DA_Ensemble model

    Processed dataset to train and test the WGAN-GP_IMOA_DA_Ensemble model by Ramya Chinnasamy (21633527)

    Published 2025
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  8. 8
    DataSheet_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx

    DataSheet_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx by Massaine Bandeira e Sousa (7866242)

    Published 2024
    “…The accuracy of the optimal scenario for classifying samples with a cooking time of 30 minutes reached RCal2  = 0.86 and RVal2 = 0.84, with a Kappa value of 0.53. …”
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  9. 9
    Table_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx

    Table_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx by Massaine Bandeira e Sousa (7866242)

    Published 2024
    “…The accuracy of the optimal scenario for classifying samples with a cooking time of 30 minutes reached RCal2  = 0.86 and RVal2 = 0.84, with a Kappa value of 0.53. …”
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