Showing 1 - 20 results of 10,463 for search 'scenario three (method OR methods)', query time: 0.31s Refine Results
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    3D Gaussian Splatting Methods for Real-World Scenarios by I. Petrovska, B. Jutzi

    Published 2025-07-01
    “…Just behind MVS, the original 3DGS implementation achieves second best accuracy results outperforming NeRFs in both scenarios, making it the most accurate 3DGS method. 3DGS-MCMC achieves the best and third best completeness for each scenario respectively, making it competitive with MVS and NeRFs in real-world setting. …”
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    Population control methods in stochastic extinction and outbreak scenarios. by Juan Segura, Frank M Hilker, Daniel Franco

    Published 2017-01-01
    “…Moreover, there is a clear disparity between the two control methods: in the extinction scenarios, ALC can be effective and ATH can be counterproductive, whereas in the outbreak scenarios the situation is reversed, with ATH being effective and ALC being potentially counterproductive.…”
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    Landslide Detection in Long-Term and Low-Coherence Scenario Using Faster Intermittent Stacking InSAR Method by Huayan Dai, Lixin Wu, Yunping Liao, Lichuan Chen, Yong Yang

    Published 2025-01-01
    “…This often leads to the minimal capability of conventional time-series InSAR methods, which poses challenges for effective ground deformation detection, particularly in low-coherence areas over long-term scenarios. …”
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    A network intrusion detection method designed for few-shot scenarios by Weichen HU, Congyuan XU, Yong ZHAN, Guanghui CHEN, Siqing LIU, Zhiqiang WANG, Xiaolin WANG

    Published 2023-10-01
    “…Existing intrusion detection techniques often require numerous malicious samples for model training.However, in real-world scenarios, only a small number of intrusion traffic samples can be obtained, which belong to few-shot scenarios.To address this challenge, a network intrusion detection method designed for few-shot scenarios was proposed.The method comprised two main parts: a packet sampling module and a meta-learning module.The packet sampling module was used for filtering, segmenting, and recombining raw network data, while the meta-learning module was used for feature extraction and result classification.Experimental results based on three few-shot datasets constructed from real network traffic data sources show that the method exhibits good applicability and fast convergence and effectively reduces the occurrence of outliers.In the case of 10 training samples, the maximum achievable detection rate is 99.29%, while the accuracy rate can reach a maximum of 97.93%.These findings demonstrate a noticeable improvement of 0.12% and 0.37% respectively, in comparison to existing algorithms.…”
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    SDGTrack: A Multi-Target Tracking Method for Pigs in Multiple Farming Scenarios by Tao Liu, Dengfei Jie, Junwei Zhuang, Dehui Zhang, Jincheng He

    Published 2025-05-01
    “…The experimental results demonstrate that SDGTrack achieved a MOTA score of 80.9%, an IDSW of 24, and an IDF1 score of 85.1% across various scenarios. Compared to the original CSTrack method, SDGTrack improved the MOTA and IDF1 scores by 16.7% and 33.3%, respectively, while significantly reducing the number of ID switches by 94.6%. …”
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    Optical sectioning methods in three-dimensional bioimaging by Jing Zhang, Wei Qiao, Rui Jin, Hongjin Li, Hui Gong, Shih-Chi Chen, Qingming Luo, Jing Yuan

    Published 2025-01-01
    “…Abstract In recent advancements in life sciences, optical microscopy has played a crucial role in acquiring high-quality three-dimensional structural and functional information. …”
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