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Showing 1 - 20 results of 108 for search '(((( query processing algorithm ) OR ( settlement data algorithm ))) OR ( level cosine algorithm ))', query time: 0.31s Refine Results
  1. 1
    Cell-TRACTR detects cells in the first frame at time t 0. Object queries predicted to be a “cell” are converted to track queries. For Track Group Denoising (TGD), random noise is added to the track queries to get noised track queries. For Query Denoising (QD), random noise is added to the ground truth bounding boxes to generate noised track queries. All queries are processed together by the decoder. Attention masks are used to prevent information leakage between the object and track queries, the noised track queries generated from TGD, and the noised track queries generated from QD. The gray boxes indicate information being blocked between sets of queries while colored boxes indicate the flow of information.

    Cell-TRACTR detects cells in the first frame at time t 0. Object queries predicted to be a “cell” are converted to track queries. For Track Group Denoising (TGD), random noise is a... by Owen M. O’Connor (11965460)

    Published 2025
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  2. 2
    City driving speed query results.

    City driving speed query results. by Meilin Zhu (688698)

    Published 2025
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  3. 3
    Cells are initially detected in frame t<sub>0</sub> and then tracked to frame t<sub>1</sub>. Object queries are processed in the first layer of the decoder for object detection. In the subsequent decoder layers, track queries are concatenated with the object queries to perform tracking.

    Cells are initially detected in frame t<sub>0</sub> and then tracked to frame t<sub>1</sub>. Object queries are processed in the first layer of the decoder for object detection. In... by Owen M. O’Connor (11965460)

    Published 2025
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  4. 4
    Number of tweets collected per query and type.

    Number of tweets collected per query and type. by Sylvia Iasulaitis (8301189)

    Published 2025
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  5. 5
    The schematic diagram of the hierarchical clustering algorithm.

    The schematic diagram of the hierarchical clustering algorithm. by Xiaojie Feng (6873953)

    Published 2025
    Subjects: “…original multidimensional data…”
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  6. 6
    Example illustrating how object and track queries interact using an attention map processed by Cell-TRACTR across two subsequent frames. The schematic displays the actual output alongside the output the from top matching object queries. Extracted from the self-attention mechanism in the decoder, the attention map highlights the strength of interactions among the queries. Lighter colors indicate stronger interactions. The track queries tend to focus on themselves, while the object queries attend to the track query that corresponds most closely in location.

    Example illustrating how object and track queries interact using an attention map processed by Cell-TRACTR across two subsequent frames. The schematic displays the actual output al... by Owen M. O’Connor (11965460)

    Published 2025
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  7. 7
    Algorithm for optimizing the model using transformer.

    Algorithm for optimizing the model using transformer. by Weiling Liu (1465480)

    Published 2025
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  8. 8
    A schematic diagram of the settlement spatial distribution model based on factor analysis integrated with the hierarchical clustering algorithm.

    A schematic diagram of the settlement spatial distribution model based on factor analysis integrated with the hierarchical clustering algorithm. by Xiaojie Feng (6873953)

    Published 2025
    Subjects: “…original multidimensional data…”
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  9. 9
    The silhouette coefficient scores for different algorithms at various levels.

    The silhouette coefficient scores for different algorithms at various levels. by Xiaojie Feng (6873953)

    Published 2025
    Subjects: “…original multidimensional data…”
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  10. 10
    Performance of ENQUIRE’s gene normalization algorithm.

    Performance of ENQUIRE’s gene normalization algorithm. by Luca Musella (19986312)

    Published 2025
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  11. 11
    The squared cosine values for the original variables in the new features (PC1 to PC5) are provided below.

    The squared cosine values for the original variables in the new features (PC1 to PC5) are provided below. by Lorenzo Serva (6184358)

    Published 2024
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  12. 12
    Flow chart of edge folding algorithm.

    Flow chart of edge folding algorithm. by Cuiying Zhou (10048078)

    Published 2025
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  13. 13
    Example of a knowledge query.

    Example of a knowledge query. by Bei Li (90587)

    Published 2025
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  14. 14
    Differences in computing performance between ENQUIRE’s gene normalization algorithm and GNorm2-Bioformer.

    Differences in computing performance between ENQUIRE’s gene normalization algorithm and GNorm2-Bioformer. by Luca Musella (19986312)

    Published 2025
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  15. 15
    Data types and sources.

    Data types and sources. by Xiaojie Feng (6873953)

    Published 2025
    Subjects: “…original multidimensional data…”
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  16. 16
    Workflow of anonymous collaboration process.

    Workflow of anonymous collaboration process. by Zhaowei Hu (9234288)

    Published 2025
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  17. 17
    The real NGD values, one-step ahead training set predictions, and multi-step ahead test set predictions using the AI-AFTER algorithm for Kayseri.

    The real NGD values, one-step ahead training set predictions, and multi-step ahead test set predictions using the AI-AFTER algorithm for Kayseri. by Burak Alakent (463512)

    Published 2025
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  18. 18
    The correlation results graph between the number of classifications (K) and the GVF for each combination.

    The correlation results graph between the number of classifications (K) and the GVF for each combination. by Xiaojie Feng (6873953)

    Published 2025
    Subjects: “…original multidimensional data…”
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  19. 19
    Comparison of grid points for each accessibility level at different time points on weekdays and weekends.

    Comparison of grid points for each accessibility level at different time points on weekdays and weekends. by Xiaojie Feng (6873953)

    Published 2025
    Subjects: “…original multidimensional data…”
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  20. 20
    The transition matrix chart for comprehensive accessibility levels on weekdays and weekends.

    The transition matrix chart for comprehensive accessibility levels on weekdays and weekends. by Xiaojie Feng (6873953)

    Published 2025
    Subjects: “…original multidimensional data…”
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