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Showing 1 - 4 results of 4 for search '(( binary hastv codon optimization algorithm ) OR ( binary data surface detection algorithm ))', query time: 0.46s Refine Results
  1. 1
    All data used to train the model is available at https://github.com/sirlis/RailDefect.

    All data used to train the model is available at https://github.com/sirlis/RailDefect. by Hailang Li (12557543)

    Published 2022
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  2. 2
    Quantile Regression and Homogeneity Identification of a Semiparametric Panel Data Model

    Quantile Regression and Homogeneity Identification of a Semiparametric Panel Data Model by Rui Li (4631)

    Published 2024
    “…<p>In this article, we delve into the quantile regression and homogeneity detection of a varying index coefficient panel data model, which incorporates fixed individual effects and exhibits nonlinear time trends. …”
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  3. 3
    PathOlOgics_RBCs Python Scripts.zip

    PathOlOgics_RBCs Python Scripts.zip by Ahmed Elsafty (16943883)

    Published 2023
    “…</p><p><br></p><p dir="ltr">In the fifth measurement technique, the numbers of sharp <b>surface projections/protrusions</b> were calculated by initially applying Canny's edge detection algorithm to generate an edge map of the cell mask image. …”
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  4. 4
    Data_Sheet_1_Predicting Brain Amyloid Using Multivariate Morphometry Statistics, Sparse Coding, and Correntropy: Validation in 1,101 Individuals From the ADNI and OASIS Databases.PDF

    Data_Sheet_1_Predicting Brain Amyloid Using Multivariate Morphometry Statistics, Sparse Coding, and Correntropy: Validation in 1,101 Individuals From the ADNI and OASIS Databases.P... by Jianfeng Wu (360829)

    Published 2021
    “…Here we attempt to use MRI-MMS to make inferences regarding brain Aβ burden at the individual subject level. As MMS data has a larger dimension than the sample size, we propose a sparse coding algorithm, Patch Analysis-based Surface Correntropy-induced Sparse-coding and Max-Pooling (PASCS-MP), to generate a low-dimensional representation of hippocampal morphometry for each individual subject. …”
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