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Showing 1 - 20 results of 34 for search '(( binary image design optimization algorithm ) OR ( library based robust optimization algorithm ))', query time: 0.62s Refine Results
  1. 1
    Illustration of the transformed binary images of normal, benign, and malignant samples into grayscale.

    Illustration of the transformed binary images of normal, benign, and malignant samples into grayscale. by Tehnan I. A. Mohamed (16846175)

    Published 2023
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  2. 2
    Data_Sheet_1_CLGBO: An Algorithm for Constructing Highly Robust Coding Sets for DNA Storage.docx

    Data_Sheet_1_CLGBO: An Algorithm for Constructing Highly Robust Coding Sets for DNA Storage.docx by Yanfen Zheng (3814507)

    Published 2021
    “…In this study, we describe an enhanced gradient-based optimizer that includes the Cauchy and Levy mutation strategy (CLGBO) to construct DNA coding sets, which are used as primer and address libraries. …”
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  3. 3
    Fine-Tuning a Genetic Algorithm for CAMD: A Screening-Guided Warm Start

    Fine-Tuning a Genetic Algorithm for CAMD: A Screening-Guided Warm Start by Yifan Wang (380120)

    Published 2025
    “…In response to these challenges, this work presents a method to fine-tune a genetic algorithm for CAMD. The proposed method builds on the COSMO-CAMD framework that utilizes a genetic algorithm for solving optimization-based molecular design problems and COSMO-RS for predicting physical properties of molecules. …”
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  4. 4
    Fine-Tuning a Genetic Algorithm for CAMD: A Screening-Guided Warm Start

    Fine-Tuning a Genetic Algorithm for CAMD: A Screening-Guided Warm Start by Yifan Wang (380120)

    Published 2025
    “…In response to these challenges, this work presents a method to fine-tune a genetic algorithm for CAMD. The proposed method builds on the COSMO-CAMD framework that utilizes a genetic algorithm for solving optimization-based molecular design problems and COSMO-RS for predicting physical properties of molecules. …”
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  5. 5
    Sample image for illustration.

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

    Published 2024
    “…Furthermore, the matching score for the test image is 0.975. The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …”
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  6. 6
    Quadratic polynomial in 2D image plane.

    Quadratic polynomial in 2D image plane. by Indhumathi S. (19173013)

    Published 2024
    “…Furthermore, the matching score for the test image is 0.975. The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …”
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  7. 7
    Priority rule-based heuristics for distributed multi-project scheduling considering global resource failures

    Priority rule-based heuristics for distributed multi-project scheduling considering global resource failures by Xuejun Hu (2003440)

    Published 2025
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  8. 8
    Comparison analysis of computation time.

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

    Published 2024
    “…Furthermore, the matching score for the test image is 0.975. The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …”
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  9. 9
    Process flow diagram of CBFD.

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

    Published 2024
    “…Furthermore, the matching score for the test image is 0.975. The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …”
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  10. 10
    Precision recall curve.

    Precision recall curve. by Indhumathi S. (19173013)

    Published 2024
    “…Furthermore, the matching score for the test image is 0.975. The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …”
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  11. 11
    Fortran & C++: design fractal-type optical diffractive element

    Fortran & C++: design fractal-type optical diffractive element by I-Lin Ho (13768960)

    Published 2022
    “…</p> <p>(2) calculate diffraction fields for fractal and/or grid-matrix (binary) phase-holograms.</p> <p>(3) optimize the fractal and/or grid-matrix holograms for given target diffraction images, using annealing algorithms. …”
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  12. 12
    Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf

    Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf by Cecilia Lindig-León (7889777)

    Published 2020
    “…And we propose two new multilabel uses of the Common Spatial Pattern (CSP) algorithm to optimize the signal-to-noise ratio, namely MC2CMI and MC2SMI approaches. …”
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  13. 13
    Predictive Analysis of Mushroom Toxicity Based Exclusively on Their Natural Habitat.

    Predictive Analysis of Mushroom Toxicity Based Exclusively on Their Natural Habitat. by Enrico Bertozzi (22461709)

    Published 2025
    “…Model evaluation was based on accuracy metrics and qualitative analysis of the confusion matrix.. …”
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  14. 14
    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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  15. 15
    Image_13_The Effect of Training Sample Size on the Prediction of White Matter Hyperintensity Volume in a Healthy Population Using BIANCA.JPEG

    Image_13_The Effect of Training Sample Size on the Prediction of White Matter Hyperintensity Volume in a Healthy Population Using BIANCA.JPEG by Niklas Wulms (11928755)

    Published 2022
    “…In this study, we tested whether WMH volumetry with FMRIB software library v6.0 (FSL; https://fsl.fmrib.ox.ac.uk/fsl/fslwiki) Brain Intensity AbNormality Classification Algorithm (BIANCA), a customizable and trainable algorithm that quantifies WMH volume based on individual data training sets, can be optimized for a normal aging population.…”
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  16. 16
    Image_2_The Effect of Training Sample Size on the Prediction of White Matter Hyperintensity Volume in a Healthy Population Using BIANCA.JPEG

    Image_2_The Effect of Training Sample Size on the Prediction of White Matter Hyperintensity Volume in a Healthy Population Using BIANCA.JPEG by Niklas Wulms (11928755)

    Published 2022
    “…In this study, we tested whether WMH volumetry with FMRIB software library v6.0 (FSL; https://fsl.fmrib.ox.ac.uk/fsl/fslwiki) Brain Intensity AbNormality Classification Algorithm (BIANCA), a customizable and trainable algorithm that quantifies WMH volume based on individual data training sets, can be optimized for a normal aging population.…”
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  17. 17
    Image_1_The Effect of Training Sample Size on the Prediction of White Matter Hyperintensity Volume in a Healthy Population Using BIANCA.JPEG

    Image_1_The Effect of Training Sample Size on the Prediction of White Matter Hyperintensity Volume in a Healthy Population Using BIANCA.JPEG by Niklas Wulms (11928755)

    Published 2022
    “…In this study, we tested whether WMH volumetry with FMRIB software library v6.0 (FSL; https://fsl.fmrib.ox.ac.uk/fsl/fslwiki) Brain Intensity AbNormality Classification Algorithm (BIANCA), a customizable and trainable algorithm that quantifies WMH volume based on individual data training sets, can be optimized for a normal aging population.…”
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  18. 18
    Image_6_The Effect of Training Sample Size on the Prediction of White Matter Hyperintensity Volume in a Healthy Population Using BIANCA.JPEG

    Image_6_The Effect of Training Sample Size on the Prediction of White Matter Hyperintensity Volume in a Healthy Population Using BIANCA.JPEG by Niklas Wulms (11928755)

    Published 2022
    “…In this study, we tested whether WMH volumetry with FMRIB software library v6.0 (FSL; https://fsl.fmrib.ox.ac.uk/fsl/fslwiki) Brain Intensity AbNormality Classification Algorithm (BIANCA), a customizable and trainable algorithm that quantifies WMH volume based on individual data training sets, can be optimized for a normal aging population.…”
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  19. 19
    Image_10_The Effect of Training Sample Size on the Prediction of White Matter Hyperintensity Volume in a Healthy Population Using BIANCA.JPEG

    Image_10_The Effect of Training Sample Size on the Prediction of White Matter Hyperintensity Volume in a Healthy Population Using BIANCA.JPEG by Niklas Wulms (11928755)

    Published 2022
    “…In this study, we tested whether WMH volumetry with FMRIB software library v6.0 (FSL; https://fsl.fmrib.ox.ac.uk/fsl/fslwiki) Brain Intensity AbNormality Classification Algorithm (BIANCA), a customizable and trainable algorithm that quantifies WMH volume based on individual data training sets, can be optimized for a normal aging population.…”
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  20. 20
    Data_Sheet_1_The Effect of Training Sample Size on the Prediction of White Matter Hyperintensity Volume in a Healthy Population Using BIANCA.pdf

    Data_Sheet_1_The Effect of Training Sample Size on the Prediction of White Matter Hyperintensity Volume in a Healthy Population Using BIANCA.pdf by Niklas Wulms (11928755)

    Published 2022
    “…In this study, we tested whether WMH volumetry with FMRIB software library v6.0 (FSL; https://fsl.fmrib.ox.ac.uk/fsl/fslwiki) Brain Intensity AbNormality Classification Algorithm (BIANCA), a customizable and trainable algorithm that quantifies WMH volume based on individual data training sets, can be optimized for a normal aging population.…”
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