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Showing 1 - 20 results of 32 for search '"vae data preprocessing"', query time: 0.11s Refine Results
  1. 1
    Working methodology of our proposed INBSI system.

    Working methodology of our proposed INBSI system. by Md. Fahim Ul Islam (22470251)

    Published 2025
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  2. 2
    Overview of the existing related models.

    Overview of the existing related models. by Md. Fahim Ul Islam (22470251)

    Published 2025
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  3. 3
    Training Loss of VAE.

    Training Loss of VAE. by Md. Fahim Ul Islam (22470251)

    Published 2025
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  4. 4
    LIME interpretibility with MLP.

    LIME interpretibility with MLP. by Md. Fahim Ul Islam (22470251)

    Published 2025
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  5. 5
    The proposed Network Bandwidth Slicing Identification (INBSI) system’s top-level paradigm.

    The proposed Network Bandwidth Slicing Identification (INBSI) system’s top-level paradigm. by Md. Fahim Ul Islam (22470251)

    Published 2025
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  6. 6
    Slice distribution using our proposed hybrid CNN model.

    Slice distribution using our proposed hybrid CNN model. by Md. Fahim Ul Islam (22470251)

    Published 2025
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  7. 7
    Training accuracy and loss curves for the DL models with our proposed model.

    Training accuracy and loss curves for the DL models with our proposed model. by Md. Fahim Ul Islam (22470251)

    Published 2025
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  8. 8
    2D PCA and t-SNE plots showing distinct clusters for network slices, indicating effective feature extraction and slice differentiation by the INBSI model.

    2D PCA and t-SNE plots showing distinct clusters for network slices, indicating effective feature extraction and slice differentiation by the INBSI model. by Md. Fahim Ul Islam (22470251)

    Published 2025
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  9. 9
    Network slicing architecture.

    Network slicing architecture. by Md. Fahim Ul Islam (22470251)

    Published 2025
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  10. 10
    Graphical representation of our proposed INBSI system.

    Graphical representation of our proposed INBSI system. by Md. Fahim Ul Islam (22470251)

    Published 2025
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  11. 11
    Confusion Matrix and Classification report for DL models and Proposed CNN Model.

    Confusion Matrix and Classification report for DL models and Proposed CNN Model. by Md. Fahim Ul Islam (22470251)

    Published 2025
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  12. 12
    Comparison of the models.

    Comparison of the models. by Md. Fahim Ul Islam (22470251)

    Published 2025
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  13. 13
    Anomaly detection of the constructed data.

    Anomaly detection of the constructed data. by Md. Fahim Ul Islam (22470251)

    Published 2025
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  14. 14
    LIME interpretability with decision tree.

    LIME interpretability with decision tree. by Md. Fahim Ul Islam (22470251)

    Published 2025
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  15. 15
    VAE performance baseline.

    VAE performance baseline. by Md. Fahim Ul Islam (22470251)

    Published 2025
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  16. 16
    Achieved scores of these models based on performance metrics.

    Achieved scores of these models based on performance metrics. by Md. Fahim Ul Islam (22470251)

    Published 2025
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  17. 17
    The proposed Model Architecture using NADAM Opitmizer.

    The proposed Model Architecture using NADAM Opitmizer. by Md. Fahim Ul Islam (22470251)

    Published 2025
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  18. 18
    3D PCA and t-SNE plots demonstrating well-separated clusters for network slices, further validating the INBSI model’s ability to learn meaningful, discriminative feature representations.

    3D PCA and t-SNE plots demonstrating well-separated clusters for network slices, further validating the INBSI model’s ability to learn meaningful, discriminative feature representa... by Md. Fahim Ul Islam (22470251)

    Published 2025
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  19. 19
    Model comparison used.

    Model comparison used. by Md. Fahim Ul Islam (22470251)

    Published 2025
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  20. 20
    Statistical Analysis of Model Performance.

    Statistical Analysis of Model Performance. by Md. Fahim Ul Islam (22470251)

    Published 2025
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