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Showing 1 - 20 results of 128 for search '(( force ((segmentation algorithm) OR (selection algorithm)) ) OR ( code encryption algorithm ))', query time: 0.39s Refine Results
  1. 1
    Optimization-Driven Steganographic System Based on Fused Maps and Blowfish Encryption

    Optimization-Driven Steganographic System Based on Fused Maps and Blowfish Encryption by Ahmed Aljughaiman (21793526)

    Published 2025
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  2. 2
    Pseudo-code for encrypting high-dimensional medical data attributes.

    Pseudo-code for encrypting high-dimensional medical data attributes. by Yonggang Huang (223155)

    Published 2025
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  3. 3
    Access control pseudo-code.

    Access control pseudo-code. by Yonggang Huang (223155)

    Published 2025
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  4. 4
    Selection of Optimum Clusters for the Sample Microscopic Image using Partition Entropy.

    Selection of Optimum Clusters for the Sample Microscopic Image using Partition Entropy. by Claudia Barile (20678698)

    Published 2025
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  5. 5
    Number of features selected.

    Number of features selected. by Islam Zada (21755819)

    Published 2025
    “…In this paper, a Lean-based hybrid Intrusion Detection framework using Particle Swarm Optimization and Genetic Algorithm (PSO-GA) to select the features and Extreme Learning Machine and Bootstrap Aggregation (ELM-BA) to classify the features is introduced. …”
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  6. 6
    Data Encryption and Compression

    Data Encryption and Compression by Chandra Shekhar Ram (20325126)

    Published 2024
    “…Advanced compression techniques, including <b>Huffman coding</b> and <b>Lempel-Ziv algorithms</b>, are covered to illustrate their practical applications in modern data systems. …”
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  7. 7
    Correlation heatmap of selected features.

    Correlation heatmap of selected features. by Islam Zada (21755819)

    Published 2025
    “…In this paper, a Lean-based hybrid Intrusion Detection framework using Particle Swarm Optimization and Genetic Algorithm (PSO-GA) to select the features and Extreme Learning Machine and Bootstrap Aggregation (ELM-BA) to classify the features is introduced. …”
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  8. 8
    Convergence curve of the DBO algorithm.

    Convergence curve of the DBO algorithm. by Ma Haohao (22177538)

    Published 2025
    “…The improved Dung Beetle Optimization algorithm, Back Propagation Neural Network, Finite Element Analysis, and Response Surface Methodology provide a strong guarantee for the selection of robot polishing process parameters. …”
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  9. 9
    Four Step Compressive Loading Cycle used to Simulate the Occlusal Contact Force during Swallowing.

    Four Step Compressive Loading Cycle used to Simulate the Occlusal Contact Force during Swallowing. by Claudia Barile (20678698)

    Published 2025
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  10. 10
    Perceptual segmentation results based on luminance, color, and spatial phase.

    Perceptual segmentation results based on luminance, color, and spatial phase. by Yen-Ju Chen (354876)

    Published 2025
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  11. 11
    Sway estimation from force platform and four inertial measurement units.

    Sway estimation from force platform and four inertial measurement units. by Liam H. Foulger (20552939)

    Published 2025
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  12. 12
    Image 2_A comparison of design algorithms for choosing the training population in genomic models.jpeg

    Image 2_A comparison of design algorithms for choosing the training population in genomic models.jpeg by Alexandra Stadler (20718002)

    Published 2025
    “…Classical exchange-type algorithms from optimal design theory can be employed for this purpose. …”
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  13. 13
    Image 8_A comparison of design algorithms for choosing the training population in genomic models.jpeg

    Image 8_A comparison of design algorithms for choosing the training population in genomic models.jpeg by Alexandra Stadler (20718002)

    Published 2025
    “…Classical exchange-type algorithms from optimal design theory can be employed for this purpose. …”
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  14. 14
    Image 7_A comparison of design algorithms for choosing the training population in genomic models.jpeg

    Image 7_A comparison of design algorithms for choosing the training population in genomic models.jpeg by Alexandra Stadler (20718002)

    Published 2025
    “…Classical exchange-type algorithms from optimal design theory can be employed for this purpose. …”
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  15. 15
    Image 3_A comparison of design algorithms for choosing the training population in genomic models.jpeg

    Image 3_A comparison of design algorithms for choosing the training population in genomic models.jpeg by Alexandra Stadler (20718002)

    Published 2025
    “…Classical exchange-type algorithms from optimal design theory can be employed for this purpose. …”
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  16. 16
    Image 10_A comparison of design algorithms for choosing the training population in genomic models.jpeg

    Image 10_A comparison of design algorithms for choosing the training population in genomic models.jpeg by Alexandra Stadler (20718002)

    Published 2025
    “…Classical exchange-type algorithms from optimal design theory can be employed for this purpose. …”
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  17. 17
    Image 4_A comparison of design algorithms for choosing the training population in genomic models.jpeg

    Image 4_A comparison of design algorithms for choosing the training population in genomic models.jpeg by Alexandra Stadler (20718002)

    Published 2025
    “…Classical exchange-type algorithms from optimal design theory can be employed for this purpose. …”
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  18. 18
    Image 6_A comparison of design algorithms for choosing the training population in genomic models.jpeg

    Image 6_A comparison of design algorithms for choosing the training population in genomic models.jpeg by Alexandra Stadler (20718002)

    Published 2025
    “…Classical exchange-type algorithms from optimal design theory can be employed for this purpose. …”
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  19. 19
    Image 5_A comparison of design algorithms for choosing the training population in genomic models.jpeg

    Image 5_A comparison of design algorithms for choosing the training population in genomic models.jpeg by Alexandra Stadler (20718002)

    Published 2025
    “…Classical exchange-type algorithms from optimal design theory can be employed for this purpose. …”
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  20. 20
    Image 1_A comparison of design algorithms for choosing the training population in genomic models.jpeg

    Image 1_A comparison of design algorithms for choosing the training population in genomic models.jpeg by Alexandra Stadler (20718002)

    Published 2025
    “…Classical exchange-type algorithms from optimal design theory can be employed for this purpose. …”
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