Showing 401 - 420 results of 1,810 for search '(( sources detection functions ) OR (( resources OR resources) detection function ))', query time: 0.30s Refine Results
  1. 401

    A Method for Extracting Features of the Intrinsic Mode Function’s Energy Arrangement Entropy in the Shaft Frequency Electric Field of Vessels by Xiaoguang Ma, Zhaolong Sun, Runxiang Jiang, Xinquan Yue, Qi Liu

    Published 2025-05-01
    “…To address the challenge of detecting low-frequency electric field signals from vessels in complex marine environments, a vessel shaft frequency electric field feature extraction method based on intrinsic mode function energy arrangement entropy values is proposed, building upon a scaled model. …”
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  2. 402

    Energy-Efficiency using Critical Nodes Detection Problem in Industrial Wireless Sensor Networks (IWSNs) by Karima MOULEY, Mohamed Amin TAHRAOUI, Abdelaziz KELLA

    Published 2025-03-01
    “…Experiments simulation validates our proposed approach, approving its efficiency in reducing significant energy consumption while preserving connectivity and functionality for industrial systems. Furthermore, the results highlight the potential of using critical node analysis to support sustainable and efficient operations in resource-constrained industrial environments. …”
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  3. 403
  4. 404

    Securing Industrial IoT Environments: A Fuzzy Graph Attention Network for Robust Intrusion Detection by Safa Ben Atitallah, Maha Driss, Wadii Boulila, Anis Koubaa

    Published 2025-01-01
    “…The Industrial Internet of Things (IIoT) faces significant cybersecurity threats due to its ever-changing network structures, diverse data sources, and inherent uncertainties, making robust intrusion detection crucial. …”
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  5. 405

    SILVERRUSH. XIV. Lyα Luminosity Functions and Angular Correlation Functions from 20,000 Lyα Emitters at z ∼ 2.2–7.3 from up to 24 deg2 HSC-SSP and CHORUS Surveys: Linking the Postr... by Hiroya Umeda, Masami Ouchi, Satoshi Kikuta, Yuichi Harikane, Yoshiaki Ono, Takatoshi Shibuya, Akio K. Inoue, Kazuhiro Shimasaku, Yongming Liang, Akinori Matsumoto, Shun Saito, Haruka Kusakabe, Yuta Kageura, Minami Nakane

    Published 2025-01-01
    “…We present luminosity functions (LFs) and angular correlation functions (ACFs) derived from 18,960 Ly α emitters (LAEs) at z  = 2.2−7.3 over a wide survey area of ≲24 deg ^2 that are identified in the narrowband data of the HSC-SSP and CHORUS surveys. …”
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  6. 406

    Dual Function Radar and Communication Waveform Design Based on Sub-pulse Hybrid Modulation by Yu LIU, Junhao ZHANG, Xue YAO, Xianxiang YU, Guolong CUI

    Published 2025-08-01
    “…To address the low data rate issue in the design of Dual-Function Radar-Communication (DFRC) waveforms with radar detection as the primary function, this paper proposes an information modulation method for multiple sub-pulse structure waveforms called Sub-pulse Hybrid Modulation (SHM). …”
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  7. 407

    Cost-Sensitive Radial Basis Function Neural Network Classifier for Software Defect Prediction by P. Kumudha, R. Venkatesan

    Published 2016-01-01
    “…Effective prediction of software modules, those that are prone to defects, will enable software developers to achieve efficient allocation of resources and to concentrate on quality assurance activities. …”
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  8. 408

    Cascaded Directional Coupler-Based Triplexer Working on Spectroscopically Relevant Wavelengths for Multiple Gas Detection by Ajmal Thottoli, Gabriele Biagi, Artem S. Vorobev, Antonella D’Orazio, Giovanni Magno, Liam O’Faolain

    Published 2025-02-01
    “…The triplexer’s functions focus on enhancing the coupling efficiency and selectivity, while facilitating the on-chip integration of diode lasers. …”
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  9. 409

    Harnessing Deep Learning With AlexNet for Tomato Leaf Disease Detection in the Indian Himalayan Terrain by Ruchika Sharma, Sameena Naaz, Pankaj Vaidya

    Published 2025-01-01
    “…Agriculture is essential for living in the Indian Himalayan region (IHR), as it functions as the main occupation and source of income. …”
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  10. 410

    CSW-YOLO: A traffic sign small target detection algorithm based on YOLOv8. by Qian Shen, Yi Li, YuXiang Zhang, Lei Zhang, ShiHao Liu, Jinhua Wu

    Published 2025-01-01
    “…The model achieves precision on par with existing mainstream algorithms, while being simpler, significantly reducing computational requirements, and being more suitable for small target detection tasks. The source code and test results of the models used in this study are available at https://github.com/lyzzzzyy/CSW-YOLO.git.…”
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  11. 411

    Detection of VOCs and Biogenic Amines Through Luminescent Zn–Salen Complex-Tethered Pyrenyl Arms by Roberta Puglisi, Caterina Testa, Sara Scuderi, Valentina Greco, Giuseppe Trusso Sfrazzetto, Manuel Petroselli, Andrea Pappalardo

    Published 2024-12-01
    “…Biogenic amines, resulting from the natural decarboxylation of amino acids, are released into the environment from both natural and industrial sources. Several methods have been developed so far to detect amines in the environment. …”
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  12. 412

    VRU-YOLO: A Small Object Detection Algorithm for Vulnerable Road Users in Complex Scenes by Yunxiang Liu, Yuqing Shi

    Published 2025-01-01
    “…Accurate detection of vulnerable road users (VRUs) is critical for enhancing traffic safety and advancing autonomous driving systems. …”
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  13. 413

    YOLO11m-SCFPose: An Improved Detection Framework for Keypoint Extraction in Cucumber Fruit Phenotyping by Huijiao Yu, Xuehui Zhang, Jun Yan, Xianyong Meng

    Published 2025-07-01
    “…The Focaler-IoU loss function is employed to improve keypoint localization accuracy. …”
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  14. 414

    The Artificial Intelligence-Enhanced Echocardiographic Detection of Congenital Heart Defects in the Fetus: A Mini-Review by Khadiza Tun Suha, Hugh Lubenow, Stefania Soria-Zurita, Marcus Haw, Joseph Vettukattil, Jingfeng Jiang

    Published 2025-03-01
    “…In this review paper, we first outline the technical background of AI and echocardiography and then present an array of clinical applications, including image quality control, cardiac function measurements, defect detection, and classifications. …”
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  15. 415
  16. 416

    Enhancing Deepfake Detection Through Quantum Transfer Learning and Class-Attention Vision Transformer Architecture by Bekir Eray Katı, Ecir Uğur Küçüksille, Güncel Sarıman

    Published 2025-01-01
    “…The model’s performance was compared with other methods evaluated on the DFDC dataset, highlighting its efficiency in resource utilization and overall effectiveness. The findings reveal that the proposed QTL-CaiT-based system provides a strong foundation for deepfake detection and contributes significantly to the academic literature. …”
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  17. 417
  18. 418

    Automated Artery Detection and Stenosis Classification in CTA Using Deep Learning for Peripheral Arterial Disease by Ali M. O. A. Anwer, Hacer Karacan, Muhammed Rabee, Levent Enver, Gonca Cabuk

    Published 2025-01-01
    “…We use Faster R-CNN with a ResNet-101 backbone driven by a custom loss function to achieve good artery localization and reduce false positives. …”
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  19. 419

    Smart Fault Detection, Classification, and Localization in Distribution Networks: AI-Driven Approaches and Emerging Technologies by Jianxian Wang, Hazlie Mokhlis, Nurulafiqah Nadzirah Mansor, Hazlee Azil Illias, Agileswari K. Ramasamy, Xingyu Wu, Siqi Wang

    Published 2025-01-01
    “…However, with nations worldwide actively pursuing carbon neutrality and emission peak goals, sustainable energy sources such as solar and wind are increasingly penetrating distribution networks, posing significant challenges to conventional fault detection, classification, and localization techniques due to bidirectional power flows, dynamic fault currents, and rising network complexity. …”
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  20. 420

    GastroEndoNet: Comprehensive endoscopy image dataset for GERD and polyp detectionMendeley Data by Abu Kowshir Bitto, Md. Hasan Imam Bijoy, Kamrul Hassan Shakil, Aka Das, Khalid Been Badruzzaman Biplob, Imran Mahmud, Syed Md. Minhaz Hossain

    Published 2025-06-01
    “…It provides an invaluable resource for developing machine learning models aimed at the automatic diagnosis, classification, and detection of GERD and polyps, potentially improving the speed and accuracy of clinical decision-making. …”
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