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Showing 1 - 20 results of 261 for search '(( one loss function optimization algorithm ) OR ( binary based work optimization algorithm ))', query time: 0.83s Refine Results
  1. 1
    Search Algorithms and Loss Functions for Bayesian Clustering

    Search Algorithms and Loss Functions for Bayesian Clustering by David B. Dahl (11761055)

    Published 2022
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  2. 2
    One advantage of our algorithm is that it is not binary in nature.

    One advantage of our algorithm is that it is not binary in nature. by Yong Kuk Kim (13955214)

    Published 2022
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  3. 3
    Comparison of details of different algorithms.

    Comparison of details of different algorithms. by Hao Wu (65943)

    Published 2024
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  4. 4
    Structure of the LMPEC algorithm model.

    Structure of the LMPEC algorithm model. by Hao Wu (65943)

    Published 2024
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  5. 5
    Sub-network model structure in the LMPEC algorithm.

    Sub-network model structure in the LMPEC algorithm. by Hao Wu (65943)

    Published 2024
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  6. 6
    Loss function variation curve.

    Loss function variation curve. by Chunhua Yang (346871)

    Published 2025
    “…Intersection over Union (IoU) is used to optimize the loss function calculation. The slice-assisted super-reasoning algorithm is integrated to improve the recognition ability of YOLOv10 network for long-distance and small-target tea. …”
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  7. 7
    GA and loss function (Loss<sub>L</sub>) parameters are optimized using their search spaces through the hyperparameter tuning.

    GA and loss function (Loss<sub>L</sub>) parameters are optimized using their search spaces through the hyperparameter tuning. by Burcu Ozek (16949357)

    Published 2024
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  8. 8
    Loss function and accuracy curve comparison.

    Loss function and accuracy curve comparison. by Dayu Zhang (710629)

    Published 2025
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  9. 9
    Training test results of different algorithms on natural scene exposure dataset.

    Training test results of different algorithms on natural scene exposure dataset. by Hao Wu (65943)

    Published 2024
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  10. 10
    GD and soft loss function (Loss<sub>S</sub>) parameters are optimized through the hyperparameter tuning process within their search spaces.

    GD and soft loss function (Loss<sub>S</sub>) parameters are optimized through the hyperparameter tuning process within their search spaces. by Burcu Ozek (16949357)

    Published 2024
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  11. 11
    Comparison of correction results of different algorithms on the data set of electrical equipment nameplate exposure.

    Comparison of correction results of different algorithms on the data set of electrical equipment nameplate exposure. by Hao Wu (65943)

    Published 2024
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  12. 12
    S1 Dataset -

    S1 Dataset - by Hao Wu (65943)

    Published 2024
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  13. 13
    Training and test results of different algorithms on uneven exposure data set of electrical equipment nameplate.

    Training and test results of different algorithms on uneven exposure data set of electrical equipment nameplate. by Hao Wu (65943)

    Published 2024
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  14. 14
    Data set of nameplate exposure of electrical equipment.

    Data set of nameplate exposure of electrical equipment. by Hao Wu (65943)

    Published 2024
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  15. 15
    Test results of different training methods.

    Test results of different training methods. by Hao Wu (65943)

    Published 2024
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  16. 16
    Schematic diagram of subpixel convolution.

    Schematic diagram of subpixel convolution. by Hao Wu (65943)

    Published 2024
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  17. 17
    Training results of data sets with different sizes.

    Training results of data sets with different sizes. by Hao Wu (65943)

    Published 2024
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  18. 18
    PS-UNet++ model structure.

    PS-UNet++ model structure. by Hao Wu (65943)

    Published 2024
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  19. 19
    Comparison of training results of data sets with different sizes.

    Comparison of training results of data sets with different sizes. by Hao Wu (65943)

    Published 2024
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  20. 20
    Network structure diagram of UNet++.

    Network structure diagram of UNet++. by Hao Wu (65943)

    Published 2024
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