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  1. 61

    Infrared Ship Detection in Complex Nearshore Scenes Based on Improved YOLOv5s by Xiuwen Liu, Mingchen Liu, Yong Yin

    Published 2025-06-01
    “…Accurate ship identification and classification are central to this objective, underscoring the critical importance of ship detection technology. However, compared to open-sea surface, dense vessel distributions and complex backgrounds in nearshore areas substantially limit detection efficacy. …”
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    Article
  2. 62

    Tea Disease Detection Method Based on Improved YOLOv8 in Complex Background by Junchen Ai, Yadong Li, Shengxiang Gao, Rongsheng Hu, Wengang Che

    Published 2025-07-01
    “…Experimental results show that the proposed YOLO-SSM algorithm has obvious advantages in accuracy and model complexity and can provide reliable theoretical support for efficient and accurate detection and identification of tea leaf diseases in natural scenes.…”
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    Article
  3. 63

    Enhanced YOLOv8 for Robust Pig Detection and Counting in Complex Agricultural Environments by Jian Li, Wenkai Ma, Yanan Wei, Tan Wang

    Published 2025-07-01
    “…Previous approaches often struggle with complex agricultural environments where lighting conditions, pig postures, and crowding levels create challenging detection scenarios. …”
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    Article
  4. 64

    YOLO-RDM: Innovative Detection Methods for Eggplants and Stems in Complex Natural Environment by Qin Liu, Zhibin Zhou, Lu Xiong, Meilian Lu, Jingwen Ouyang

    Published 2025-01-01
    “…To achieve rapid identification of eggplants and stems in complex environments and enhance overall accuracy, this study establishes a database for eggplants and stems and proposes an efficient detection model based on the YOLOv8n network. …”
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  5. 65
  6. 66

    An enhanced lightweight model for apple leaf disease detection in complex orchard environments by Ge Wang, Wenjie Sang, Fangqian Xu, Yuteng Gao, Yue Han, Qiang Liu

    Published 2025-03-01
    “…However, in complex natural environments, factors such as light variations, shading from branches and leaves, and overlapping disease spots often result in reduced accuracy in detecting apple diseases. …”
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    Article
  7. 67

    Binocular Vision-Based Target Detection Algorithm by Huiguo Zhang

    Published 2025-01-01
    “…In this study, the Feffol network model is proposed to achieve excellent performance in complex detection tasks. In the feature extraction stage, the Feffol network model carefully chooses Efficient-v2 as the backbone network structure, which can provide a solid foundation for subsequent detection by taking advantage of its efficient feature extraction capability. …”
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    Article
  8. 68

    GLS-YOLO: A Lightweight Tea Bud Detection Model in Complex Scenarios by Shanshan Li, Zhe Zhang, Shijun Li

    Published 2024-12-01
    “…To address the demand for high-precision yet lightweight tea bud detection, this study proposes the GLS-YOLO detection model, based on YOLOv8. …”
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    Article
  9. 69

    A review: Multi-Objective Algorithm for Community Detection in Complex Social Networks by Mariwan Wahid Ahmed, Kamaran Faraj

    Published 2025-02-01
    “…Recently, research on multi-objective optimization algorithms for community detection in complex networks has grown considerably. …”
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    Article
  10. 70

    Application of GPR Underground Pipeline Detection Technology in Urban Complex Geological Environments by Xiaoqiang Liang, Da Hu, Yongsuo Li, Yunyi Zhang, Xian Yang

    Published 2022-01-01
    “…This research applies bottom detection radar to urban underground pipeline detection technology under complex conditions for the first time, innovatively uses the action mechanism of bottom detection radar, integrates its high precision and high efficiency into underground pipeline detection technology, and ensures the effectiveness of the detection work.…”
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    Article
  11. 71

    Robust Miner Detection in Challenging Underground Environments: An Improved YOLOv11 Approach by Yadong Li, Hui Yan, Dan Li, Hongdong Wang

    Published 2024-12-01
    “…The Efficient Channel Attention (ECA) mechanism was integrated into the YOLOv11 model to enhance the model’s ability to focus on key features, thereby significantly improving detection accuracy. …”
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    Article
  12. 72

    Enhancing wind turbine blade damage detection with YOLO-Wind by Zhao Zhanfang, Li Tuo

    Published 2025-05-01
    “…Furthermore, a newly added P2 detection layer enhances multi-scale defect recognition in complex environments. …”
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    Article
  13. 73

    Efficient Small Object Detection You Only Look Once: A Small Object Detection Algorithm for Aerial Images by Jie Luo, Zhicheng Liu, Yibo Wang, Ao Tang, Huahong Zuo, Ping Han

    Published 2024-11-01
    “…We propose an efficient small-object YOLO detection model (ESOD-YOLO) based on YOLOv8n for Unmanned Aerial Vehicle (UAV) object detection. …”
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  14. 74

    Incorporating long-tail data in complex backgrounds for visual surface defect detection in PCBs by Liying Zhu, Sen Wang, Mingfang Chen, Aiping Shen, Xuangang Li

    Published 2024-07-01
    “…Nevertheless, most of the existing methods for PCB surface defect detection neglect the fact that PCB surface defects in complex backgrounds are prone to long-tailed data distributions, which in turn affects the effectiveness of defect detection. …”
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  15. 75
  16. 76

    An FPGA Prototype for Parkinson’s Disease Detection Using Machine Learning on Voice Signal by Mujeev Khan, Abdul Moiz, Gani Nawaz Khan, Mohd Wajid, Mohammed Usman, Jabir Ali

    Published 2025-01-01
    “…This paper proposes an efficient machine learning model for PD detection using voice-based features, which offer a non-invasive, cost-effective, and accessible alternative to complex imaging methods. …”
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    Article
  17. 77

    EfficientTransformer: A Dynamic Anomaly Detection Model for Industrial Control Networks by Jinyang Liu, Guogang Wang, Xuejun Zong, Bowei Ning, Kan He

    Published 2025-01-01
    “…This reduces computational complexity and enables efficient parallel learning. …”
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    Article
  18. 78

    FoT: an efficient transformer framework for real-time small object detection in football videos by Wentao Zhang, Yaocong Yang

    Published 2025-08-01
    “…Abstract Football videos are playing an increasingly important role in event analysis and tactical evaluation within computer vision. Traditional object detection methods, relying on region proposals and anchor generation, struggle to balance real-time performance and accuracy in complex scenarios such as multi-view, motion blur, and small object recognition. …”
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  19. 79

    SCoralDet: Efficient real-time underwater soft coral detection with YOLO by Zhaoxuan Lu, Lyuchao Liao, Xingang Xie, Hui Yuan

    Published 2025-03-01
    “…In recent years, climate change and marine pollution have significantly degraded coral reefs, highlighting the urgent need for automated coral detection to monitor marine ecosystems. However, underwater coral detection presents unique challenges, including low image contrast, complex coral structures, and dense coral growth, which limit the effectiveness of general object detection algorithms. …”
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  20. 80

    SD-YOLO: A Robust and Efficient Object Detector for Aerial Image Detection by Shuaihui Qi, Yi Sun, Xiaofeng Song, Jiting Li, Tongfei Shang, Li Yu

    Published 2025-01-01
    “…Aerial image detection remains challenging due to the varying scales of objects and complex backgrounds. …”
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    Article