Showing 101 - 112 results of 112 for search '(( binary image codon optimization algorithm ) OR ( binary 2 based optimization algorithm ))*', query time: 0.40s Refine Results
  1. 101

    Steps in the extraction of 14 coordinates from the CT slices for the curved MPR. by Linus Woitke (22783534)

    Published 2025
    “…Protruding paths are then eliminated using graph-based optimization algorithms, as demonstrated in f). …”
  2. 102

    Active Learning Accelerated Discovery of Stable Iridium Oxide Polymorphs for the Oxygen Evolution Reaction by Raul A. Flores (2910539)

    Published 2020
    “…Herein, we report a readily generalizable active-learning (AL) accelerated algorithm for identification of electrochemically stable iridium oxide polymorphs of IrO<sub>2</sub> and IrO<sub>3</sub>. …”
  3. 103

    Sample image for illustration. by Indhumathi S. (19173013)

    Published 2024
    “…The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …”
  4. 104

    Comparison analysis of computation time. by Indhumathi S. (19173013)

    Published 2024
    “…The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …”
  5. 105

    Process flow diagram of CBFD. by Indhumathi S. (19173013)

    Published 2024
    “…The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …”
  6. 106

    Precision recall curve. by Indhumathi S. (19173013)

    Published 2024
    “…The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …”
  7. 107

    Table_1_iRNA5hmC: The First Predictor to Identify RNA 5-Hydroxymethylcytosine Modifications Using Machine Learning.docx by Yuan Liu (88411)

    Published 2020
    “…In this predictor, we introduced a sequence-based feature algorithm consisting of two feature representations, (1) k-mer spectrum and (2) positional nucleotide binary vector, to capture the sequential characteristics of 5hmC sites. …”
  8. 108

    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. …”
  9. 109

    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. …”
  10. 110

    DataSheet_1_Exploring deep learning radiomics for classifying osteoporotic vertebral fractures in X-ray images.docx by Jun Zhang (48506)

    Published 2024
    “…The OVFs were categorized as class 0, 1, or 2 based on the Assessment System of Thoracolumbar Osteoporotic Fracture. …”
  11. 111

    Seed mix selection model by Bethanne Bruninga-Socolar (10923639)

    Published 2022
    “…</p> <p>  </p> <p>We applied the seed mix selection model using a binary genetic algorithm to select seed mixes (R package ‘GA’; Scrucca 2013; Scrucca 2017). …”
  12. 112

    Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles by Soham Savarkar (21811825)

    Published 2025
    “…</p><p dir="ltr">These biological metrics were used to define a binary toxicity label: entries were classified as toxic (1) or non-toxic (0) based on thresholds from standardized guidelines (e.g., ISO 10993-5:2009) and literature consensus. …”