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Showing 1 - 20 results of 426 for search '(((( element processing algorithm ) OR ( elements b algorithm ))) OR ( neural coding algorithm ))', query time: 0.62s Refine Results
  1. 1
    Comparison of different optimization algorithms.

    Comparison of different optimization algorithms. by Hang Zhao (143592)

    Published 2025
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  2. 2
    ML algorithms in cyber security.

    ML algorithms in cyber security. by Abdullah Asım Yılmaz (20715311)

    Published 2025
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  3. 3
    A detailed process of iterative simulation coupled with bone density algorithm; (a) a function of stimulus and related bone density changes, and (b) iterative calculations of finite element analysis coupled with user’s subroutine for changes in bone density.

    A detailed process of iterative simulation coupled with bone density algorithm; (a) a function of stimulus and related bone density changes, and (b) iterative calculations of finite element analysis coupled with user’s subroutine for changes in bone density. by Hassan Mehboob (8960273)

    Published 2025
    “…<p>A detailed process of iterative simulation coupled with bone density algorithm; (a) a function of stimulus and related bone density changes, and (b) iterative calculations of finite element analysis coupled with user’s subroutine for changes in bone density.…”
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  4. 4
    Dataset for Fine-Tuning Code Generation Models: Kannada-English Algorithmic Statements and Python Code

    Dataset for Fine-Tuning Code Generation Models: Kannada-English Algorithmic Statements and Python Code by Goutami Sooda (20714729)

    Published 2025
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  5. 5
    (A) Illustration of grouping and segmentation based on the global similarity structure when the number of elements is small. A, B, C, and D represent stimulus elements at different spatial locations. The physical pairwise similarities are assumed to be high between A and B and between C and D, while they are relatively low for the other four pairs, as indicated by the physical similarity matrix. This configuration potentially leads to the grouping of {A, B} and {C, D}, as depicted by the dashed red squares. Following neural processing that incorporates the global similarity structure, similar pairs are grouped, whereas dissimilar pairs are segregated, as reflected in the perceptual connection matrix. (B) Demonstration of how computational complexity increases with stimulus size. The left panel presents the physical similarity matrix for 3 × 6 and 4 × 8 element stimuli, respectively. The right panel illustrates the exponential growth in the number o

    (A) Illustration of grouping and segmentation based on the global similarity structure when the number of elements is small. A, B, C, and D represent stimulus elements at different... by Yen-Ju Chen (354876)

    Published 2025
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  6. 6
    Data and code resources.

    Data and code resources. by Sam Hall-McMaster (10343795)

    Published 2025
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  7. 7
    Process followed to develop and validate the MAMELI algorithm.

    Process followed to develop and validate the MAMELI algorithm. by Valentina Bollati (106778)

    Published 2025
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  8. 8
    <b>Robot_gripper_design</b>

    <b>Robot_gripper_design</b> by Ma Haohao (19780875)

    Published 2024
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  9. 9
    The parameter setting of the evolutionary neural network.

    The parameter setting of the evolutionary neural network. by Wenbing Shi (5806160)

    Published 2025
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  10. 10
    The genome coding scheme.

    The genome coding scheme. by Wenbing Shi (5806160)

    Published 2025
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  11. 11
    <b>Discrimination of gold deposit types based on big data analysis and machine learning techniques</b>

    <b>Discrimination of gold deposit types based on big data analysis and machine learning techniques</b> by Lihao Feng (20837036)

    Published 2025
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  12. 12
    Stress Nephogram of the Splitting Specimen Process.

    Stress Nephogram of the Splitting Specimen Process. by Nan Ru (9594384)

    Published 2025
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  13. 13
    Flowchart of Random Aggregate Placement Process.

    Flowchart of Random Aggregate Placement Process. by Nan Ru (9594384)

    Published 2025
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  14. 14
    The optimal number of clusters identified using the GMM clustering algorithm.

    The optimal number of clusters identified using the GMM clustering algorithm. by Dinh K. Tang (20469082)

    Published 2024
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  15. 15
    Optimal number of clusters identified using the GMM clustering algorithm.

    Optimal number of clusters identified using the GMM clustering algorithm. by Dinh K. Tang (20469082)

    Published 2024
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  16. 16
    Impact of multiunit merging on neural information encoding.

    Impact of multiunit merging on neural information encoding. by Daniel Suárez-Barrera (22676654)

    Published 2025
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  17. 17
    Codes for "<b>A coherent power-load optimization algorithm for wind-farm-level yaw control considering wake effects via deep neural network</b>"

    Codes for "<b>A coherent power-load optimization algorithm for wind-farm-level yaw control considering wake effects via deep neural network</b>" by Yize Wang (19535173)

    Published 2024
    “…<p dir="ltr">Codes for "<b>A coherent power-load optimization algorithm for wind-farm-level yaw control considering wake effects via deep neural network</b>"</p>…”
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  18. 18
    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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  19. 19
    code_4

    code_4 by Olga Ovtsarenko (20432033)

    Published 2024
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  20. 20
    Schematic diagram of the experimental algorithm.

    Schematic diagram of the experimental algorithm. by Ronghua Meng (20978441)

    Published 2025
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