Showing 281 - 300 results of 22,558 for search 'detection sampling', query time: 0.17s Refine Results
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    Sample selection using multi-task autoencoders in federated learning with non-IID data by Emre Ardıç, Yakup Genç

    Published 2025-01-01
    “…Our approach incorporates unsupervised outlier detection, using one-class support vector machine (OCSVM), isolation forest (IF), and adaptive loss threshold (AT) methods managed by a central server to filter noisy samples on clients. …”
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  4. 284

    Letter to the editor: ‘Implementation of facemask sampling for the detection of infectious individuals with SARS-CoV-2 in high stakes clinical examinations – a feasibility study’ by Hinpetch Daungsupawong, Viroj Wiwanitkit

    Published 2025-03-01
    “…This is a discussion on implementation of facemask sampling for the detection of infectious individuals with SARS-CoV-2 in high-stakes clinical examinations. …”
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    A novel similarity-constrained feature selection method for epilepsy detection via EEG signals by Chunlei Shi, Jun Gao, Jian Yu, Lingzhi Zhao, Faxian Jia

    Published 2025-07-01
    “…First, the notion of sample similarity is introduced, and intra-class similarity and inter-class similarity are defined. …”
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    Detection of Obstacle Intrusion in Front of Train Based on Vehicle-borne LiDAR by ZENG Xiang, JIANG Guotao, PAN Wenbo, LENG Binghan, CHEN Guibin

    Published 2023-02-01
    “…This paper proposes a method to detect obstacle intrusion in front of the trains based on vehicle-borne LiDAR. …”
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    More Frequent Spaceborne Sampling of XCO2 Improves Detectability of Carbon Cycle Seasonal Transitions in Arctic‐Boreal Ecosystems by Nicholas C. Parazoo, Gretchen Keppel‐Aleks, Stanley Sander, Brendan Byrne, Vijay Natraj, Ming Luo, Jean‐Francois Blavier, Len Dorsky, Ray Nassar

    Published 2024-06-01
    “…Our simulations demonstrate the potential benefits of increased CO2 sampling for detecting emissions during the early cold season.…”
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    An ensemble learning method with GAN-based sampling and consistency check for anomaly detection of imbalanced data streams with concept drift. by Yansong Liu, Shuang Wang, He Sui, Li Zhu

    Published 2024-01-01
    “…A challenge to many real-world data streams is imbalance with concept drift, which is one of the most critical tasks in anomaly detection. Learning nonstationary data streams for anomaly detection has been well studied in recent years. …”
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