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Showing 1 - 20 results of 516 for search '(((( element new algorithm ) OR ( query processing algorithm ))) OR ( neural making algorithm ))', query time: 0.40s Refine Results
  1. 1
    City driving speed query results.

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

    Published 2025
    “…Firstly, from the perspective of data-driven, it crawls the historical data of driving speed through Baidu map big data platform, and uses a BP neural network optimized by genetic algorithm to predict the driving speed of vehicles in different periods. …”
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  2. 2
    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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  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
    MEA-BP neural network algorithm flowchart.

    MEA-BP neural network algorithm flowchart. by Dongling Ma (1269888)

    Published 2025
    “…A multi-population genetic algorithm (MEA) was used to optimize the weights and thresholds of a backpropagation (BP) neural network for case adaptation and reuse. …”
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  5. 5
    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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  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
    Proposed Algorithm.

    Proposed Algorithm. by Hend Bayoumi (22693738)

    Published 2025
    Subjects:
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  8. 8
    Performance of ENQUIRE’s gene normalization algorithm.

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

    Published 2025
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  9. 9
    Performance of different machine learning algorithms.

    Performance of different machine learning algorithms. by Apichat Suratanee (634281)

    Published 2024
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  10. 10
    Example of a knowledge query.

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

    Published 2025
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  11. 11
    Neural network prediction of per-time heart sound categories.

    Neural network prediction of per-time heart sound categories. by Andrew McDonald (2307400)

    Published 2024
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  12. 12
    The effectiveness of the XGBoost algorithm.

    The effectiveness of the XGBoost algorithm. by Shenglan Tang (707472)

    Published 2024
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  13. 13
    Performance comparison of different models for neural decision prediction.

    Performance comparison of different models for neural decision prediction. by Yuhang Zhang (3144870)

    Published 2025
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  14. 14
    Key features of the XGBoost algorithm.

    Key features of the XGBoost algorithm. by Shenglan Tang (707472)

    Published 2024
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  15. 15
    The working principle of the XGBoost algorithm.

    The working principle of the XGBoost algorithm. by Shenglan Tang (707472)

    Published 2024
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  16. 16
    Flowchart of DQN algorithm.

    Flowchart of DQN algorithm. by Jiandong Qiu (20389944)

    Published 2025
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  17. 17
    Comparison of different algorithms.

    Comparison of different algorithms. by Jiandong Qiu (20389944)

    Published 2025
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  18. 18
    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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  19. 19
    ML algorithms in cyber security.

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

    Published 2025
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  20. 20
    Risk element category diagram.

    Risk element category diagram. by Yao Hu (3479972)

    Published 2025
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