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Showing 1 - 20 results of 22 for search '(( tiny model process optimization algorithm ) OR ( binary time scale optimization algorithm ))', query time: 0.52s Refine Results
  1. 1
    Homomorphic binary tree.

    Homomorphic binary tree. by Jianhua He (341366)

    Published 2024
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  2. 2
    Optimization of tracking parameters based on <i>P</i><sub><i>swap</i></sub>.

    Optimization of tracking parameters based on <i>P</i><sub><i>swap</i></sub>. by Benjamin Gallois (10131683)

    Published 2021
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  3. 3
    Differences between models of different scales.

    Differences between models of different scales. by Daoze Tang (20454615)

    Published 2024
    “…To address these issues, we propose an improved, lightweight algorithm: LCFF-Net. First, we propose the LFERELAN module, designed to enhance the extraction of tiny target features and optimize the use of computational resources. …”
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  4. 4
    Microsoft excel file containing exhaustive list of Abbreviated-Injury Scale codes used to generate binary variables encoding the presence or absence of injury to various body regions/organ systems.

    Microsoft excel file containing exhaustive list of Abbreviated-Injury Scale codes used to generate binary variables encoding the presence or absence of injury to various body regio... by Michael D. Cobler-Lichter (22492930)

    Published 2025
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  5. 5
    LC-FPN structure.

    LC-FPN structure. by Daoze Tang (20454615)

    Published 2024
    “…To address these issues, we propose an improved, lightweight algorithm: LCFF-Net. First, we propose the LFERELAN module, designed to enhance the extraction of tiny target features and optimize the use of computational resources. …”
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  6. 6
    Labeling information of the VisDrone dataset.

    Labeling information of the VisDrone dataset. by Daoze Tang (20454615)

    Published 2024
    “…To address these issues, we propose an improved, lightweight algorithm: LCFF-Net. First, we propose the LFERELAN module, designed to enhance the extraction of tiny target features and optimize the use of computational resources. …”
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  7. 7
    LFERELAN structure.

    LFERELAN structure. by Daoze Tang (20454615)

    Published 2024
    “…To address these issues, we propose an improved, lightweight algorithm: LCFF-Net. First, we propose the LFERELAN module, designed to enhance the extraction of tiny target features and optimize the use of computational resources. …”
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  8. 8
    The experimental environment.

    The experimental environment. by Daoze Tang (20454615)

    Published 2024
    “…To address these issues, we propose an improved, lightweight algorithm: LCFF-Net. First, we propose the LFERELAN module, designed to enhance the extraction of tiny target features and optimize the use of computational resources. …”
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  9. 9
    LCFF-Net network structure.

    LCFF-Net network structure. by Daoze Tang (20454615)

    Published 2024
    “…To address these issues, we propose an improved, lightweight algorithm: LCFF-Net. First, we propose the LFERELAN module, designed to enhance the extraction of tiny target features and optimize the use of computational resources. …”
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  10. 10
    LDSCD-Head structure.

    LDSCD-Head structure. by Daoze Tang (20454615)

    Published 2024
    “…To address these issues, we propose an improved, lightweight algorithm: LCFF-Net. First, we propose the LFERELAN module, designed to enhance the extraction of tiny target features and optimize the use of computational resources. …”
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  11. 11
    Ablation experiment result on VisDrone-val.

    Ablation experiment result on VisDrone-val. by Daoze Tang (20454615)

    Published 2024
    “…To address these issues, we propose an improved, lightweight algorithm: LCFF-Net. First, we propose the LFERELAN module, designed to enhance the extraction of tiny target features and optimize the use of computational resources. …”
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  12. 12
    The key parameter configurations.

    The key parameter configurations. by Daoze Tang (20454615)

    Published 2024
    “…To address these issues, we propose an improved, lightweight algorithm: LCFF-Net. First, we propose the LFERELAN module, designed to enhance the extraction of tiny target features and optimize the use of computational resources. …”
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  13. 13
    LR-NET structure.

    LR-NET structure. by Daoze Tang (20454615)

    Published 2024
    “…To address these issues, we propose an improved, lightweight algorithm: LCFF-Net. First, we propose the LFERELAN module, designed to enhance the extraction of tiny target features and optimize the use of computational resources. …”
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  14. 14
    Fig 3 -

    Fig 3 - by Ali Ahmed (2567584)

    Published 2020
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  15. 15
    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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  16. 16
    Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment

    Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment by Jianfang Cao (1881379)

    Published 2019
    “…The MapReduce parallel programming model on the Hadoop platform is used to perform an adaptive fusion of hue, local binary pattern (LBP) and scale-invariant feature transform (SIFT) features extracted from images to derive optimal combinations of weights. …”
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  17. 17
    Data_Sheet_1_A real-time driver fatigue identification method based on GA-GRNN.ZIP

    Data_Sheet_1_A real-time driver fatigue identification method based on GA-GRNN.ZIP by Xiaoyuan Wang (492534)

    Published 2022
    “…In this paper, a non-invasive and low-cost method of fatigue driving state identification based on genetic algorithm optimization of generalized regression neural network model is proposed. …”
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  18. 18
    Data_Sheet_1_Physics-Inspired Optimization for Quadratic Unconstrained Problems Using a Digital Annealer.pdf

    Data_Sheet_1_Physics-Inspired Optimization for Quadratic Unconstrained Problems Using a Digital Annealer.pdf by Maliheh Aramon (6557906)

    Published 2019
    “…Our results suggest an improved scaling over the other algorithms for fully connected problems of average difficulty with bimodal disorder. …”
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  19. 19
    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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  20. 20
    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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