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  1. 541

    Enhancing Drone Detection via Transformer Neural Network and Positive–Negative Momentum Optimizers by Pavel Lyakhov, Denis Butusov, Vadim Pismennyy, Ruslan Abdulkadirov, Nikolay Nagornov, Valerii Ostrovskii, Diana Kalita

    Published 2025-06-01
    “…The developed algorithms for training NN architectures improved the accuracy of drone detection by achieving the global extremum of the loss function in fewer epochs using positive–negative pulse-based optimization algorithms. …”
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    Article
  2. 542

    A lightweight UAV target detection algorithm based on improved YOLOv8s model by Fubao Ma, Ran Zhang, Bowen Zhu, Xirui Yang

    Published 2025-05-01
    “…Furthermore, the original loss function is replaced with SIoU to enhance detection accuracy. …”
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    Article
  3. 543

    A Lightweight Network for UAV Multi-Scale Feature Fusion-Based Object Detection by Sheng Deng, Yaping Wan

    Published 2025-03-01
    “…To tackle the issues of small target sizes, missed detections, and false alarms in aerial drone imagery, alongside the constraints posed by limited hardware resources during model deployment, a streamlined object detection approach is proposed to enhance the performance of YOLOv8s. …”
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    Article
  4. 544

    Research on underwater disease target detection method of inland waterway based on deep learning by Tao Yu, Yu Xie, Jinsong Luo, Wei Zhu, Jie Liu

    Published 2025-04-01
    “…Abstract Aiming at the problems of low detection accuracy and poor generalization ability of underwater disease targets in inland waterways, an underwater disease target detection algorithm for inland waterways based on improved YOLOv5 is designed, which is denoted as YOLOv5-GBCE. …”
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    Article
  5. 545

    STAR-YOLO: A High-Accuracy and Ultra-Lightweight Method for Brain Tumor Detection by Liyan Sun, Linxuan Zheng, Zhiguo Xiao, Yi Xin, Linqing Jiang

    Published 2025-01-01
    “…STAR-YOLO accomplishes a lightweight design while guaranteeing high detection accuracy, prominently demonstrating its immense potential in the diagnosis of clinical brain tumors, particularly in circumstances with constrained computing resources.…”
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  6. 546

    GSF-YOLOv8: A Novel Approach for Fire Detection Using Gather-Distribute Mechanism and SimAM Attention by Caixiong Li, Dali Wu, Xing Zhang, Peng Wu

    Published 2025-01-01
    “…To address the current challenges in fire detection algorithms, including insufficient feature extraction, high computational complexity, limited deployment on resource-constrained devices, missed detections, false detections, and low accuracy, we developed a high-precision algorithm named GSF-YOLOv8. …”
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  7. 547

    YOLOLS: A Lightweight and High-Precision Power Insulator Defect Detection Network for Real-Time Edge Deployment by Qinglong Wang, Zhengyu Hu, Entuo Li, Guyu Wu, Wengang Yang, Yunjian Hu, Wen Peng, Jie Sun

    Published 2025-03-01
    “…However, deploying deep learning models on edge devices presents significant challenges due to limited computational resources and strict latency constraints. To address these issues, we propose YOLOLS, a lightweight and efficient detection model derived from YOLOv8n and optimized for real-time edge deployment. …”
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    Article
  8. 548

    Features of Bearing on Underwater Object Using Phase Information of a Differential Stereo Sensor by V. A. Shirokov, A. I. Bazhenova, V. N. Milich

    Published 2024-06-01
    “…Safety of navigation and development of underwater mineral deposits require the accurate detection of various underwater objects. The literature discusses the issues of tracking their motion and trajectory. …”
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  9. 549
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  11. 551

    Enhanced Intrusion Detection in In-Vehicle Networks Using Advanced Feature Fusion and Stacking-Enriched Learning by Ali Altalbe

    Published 2024-01-01
    “…To address this problem, machine learning (ML) based intrusion detection systems (IDSs) have been proposed. However, existing IDSs suffer from low detection accuracy, limited real-time response, and high resource requirements. …”
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  12. 552
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  14. 554

    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
    “…We envision that, through the combination of tele-echocardiography and AI, low-resource medical facilities may gain access to the effective detection of CHD at the prenatal stage.…”
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    Article
  15. 555

    A Heterogeneity-Aware Semi-Decentralized Model for a Lightweight Intrusion Detection System for IoT Networks Based on Federated Learning and BiLSTM by Shuroog Alsaleh, Mohamed El Bachir Menai, Saad Al-Ahmadi

    Published 2025-02-01
    “…Most IoT devices have limited resource capabilities (e.g., memory capacity, processing power, and energy consumption) to function as conventional intrusion detection systems (IDSs). …”
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  16. 556
  17. 557

    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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  18. 558

    Machine learning-based model for acute asthma exacerbation detection using routine blood parameters by Youpeng Chen, Junquan Sun, Yabang Chen, Enzhong Li, Jiancai Lu, Huanhua Tang, Yifei Xie, Jiana Zhang, Lesi Peng, Haojie Wu, Zhangkai J. Cheng, Baoqing Sun

    Published 2025-07-01
    “…Background: Acute asthma exacerbations (AAEs) are a leading cause of asthma-related morbidity and mortality, especially in resource-limited settings where pulmonary function tests are unavailable or when patients are unable to cooperate with testing. …”
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  19. 559

    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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  20. 560

    Simple Single-Person Fall Detection Model Using 3D Pose Estimation Mechanisms by Jinmo Yang, R. Young Chul Kim

    Published 2024-01-01
    “…Although various technologies with wearables and vision systems that utilize artificial intelligence (AI) have been developed to detect falls, many AI models are complex and resource-intensive. …”
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