Showing 101 - 120 results of 2,109 for search 'low detection algorithm', query time: 0.12s Refine Results
  1. 101

    Advancing Rice Disease Detection in Farmland with an Enhanced YOLOv11 Algorithm by Hongxin Teng, Yudi Wang, Wentao Li, Tao Chen, Qinghua Liu

    Published 2025-05-01
    “…The algorithm offers significant advantages in lightweight design and real-time performance, outperforming other classical object detection algorithms and providing an optimal solution for real-time field diagnosis.…”
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    Article
  2. 102

    A Novel Community Detection Algorithm Based on Node Propagation and Attraction by Lidong Fu, Xinxing Xie, Zengfa Dou, Yun Bai, Xi Zhao

    Published 2025-01-01
    “…To address this problem, this paper proposes a novel community detection algorithm based on node propagation and attraction. …”
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    Article
  3. 103
  4. 104

    The Application of Kalman Filter Algorithm in Rail Transit Signal Safety Detection by Zhinong Miao, Qilong Liao

    Published 2025-01-01
    “…Therefore, research is being conducted to optimize the signal safety detection system for rail transit. Firstly, the improved Kalman filter algorithm is used to denoise the signal to ensure the accuracy of signal transmission. …”
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    Article
  5. 105
  6. 106

    Lightweight defect detection algorithm of tunnel lining based on knowledge distillation by Anfu Zhu, Jiaxiao Xie, Bin Wang, Heng Guo, Zilong Guo, Jie Wang, Lei Xu, SiXin Zhu, Zhanping Yang

    Published 2024-11-01
    “…Aiming at the problems of complex detection model, poor real-time performance and low accuracy of the current tunnel lining defect detection methods, the study proposes a lightweight defect detection algorithm of tunnel lining based on knowledge distillation. …”
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    Article
  7. 107

    Research on Fire Smoke Detection Algorithm Based on Improved YOLOv8 by Tianxin Zhang, Fuwei Wang, Weimin Wang, Qihao Zhao, Weijun Ning, Haodong Wu

    Published 2024-01-01
    “…The susceptibility of existing fire detection technologies to background interference frequently results in false alarms, missed detections, and low detection accuracy. …”
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    Article
  8. 108

    Study on Lightweight Bridge Crack Detection Algorithm Based on YOLO11 by Xuwei Dong, Jiashuo Yuan, Jinpeng Dai

    Published 2025-05-01
    “…Traditional detection methods often suffer from low efficiency and insufficient accuracy. …”
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    Article
  9. 109

    CTDA: an accurate and efficient cherry tomato detection algorithm in complex environments by Zhi Liang, Caihong Zhang, Zhonglong Lin, Guoqiang Wang, Xiaojuan Li, Xiangjun Zou

    Published 2025-03-01
    “…To ensure accuracy and efficiency in detecting cherry tomatoes in complex environments, the study proposes a precise, realtime, and robust target detection algorithm: the CTDA model, to support robotic harvesting operations in unstructured environments.MethodsThe model, based on YOLOv8, introduces a lightweight downsampling method to restructure the backbone network, incorporating adaptive weights and receptive field spatial characteristics to ensure that low-dimensional small target features are not completely lost. …”
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  10. 110

    Statistically Bounding Detection Latency in Low-Duty-Cycled Sensor Networks by Yanmin Zhu

    Published 2012-02-01
    “…This paper studies the fundamental problem of bounding detection delays when the sensor network is low duty cycled. …”
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  11. 111

    Low-Illumination Parking Scenario Detection Based on Image Adaptive Enhancement by Xixi Xu, Meiqi Zhang, Hao Tang, Weiye Xu, Bowen Sun, Zhu’an Zheng

    Published 2025-05-01
    “…Aiming at the problem of easily missed and misdetected parking spaces and obstacles in the automatic parking perception task under low-illumination conditions, this paper proposes a low-illumination parking space and obstacle detection algorithm based on image adaptive enhancement. …”
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  12. 112

    Enhanced object detection in low-visibility haze conditions with YOLOv9s. by Yang Zhang, Bin Zhou, Xue Zhao, Xiaomeng Song

    Published 2025-01-01
    “…Low-visibility haze environments, marked by their inherent low contrast and high brightness, present a formidable challenge to the precision and robustness of conventional object detection algorithms. …”
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  13. 113

    Lightweight YOLO models for object detection based on low-rank decomposition by LIN Delü, LIU Chang, CHEN Qi, ZENG Yang, HE Kun

    Published 2024-01-01
    “…This paper proposed a parameter compression algorithm based on low-rank decomposition for the You Only Look Once (YOLO) series of object detection models, aiming to overcome the limited versatility of current lightweight treatment methods for these models. …”
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  14. 114

    Low Complexity Optimized AOR Method for Massive MIMO Signal Detection by Muhammad Nauman Irshad, Muhamamd Muzamil Aslam, Rardchawadee Silapunt

    Published 2025-01-01
    “…To determine these parameters systematically, we incorporate an innovative approach using the Nelder-Mead Simplex optimization algorithm. This heuristic optimization technique allows us to find the optimal acceleration and relaxation parameters, thereby achieving superior detection accuracy with faster convergence for challenging system configurations. …”
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  15. 115
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  17. 117

    Replica Node Detection Using Enhanced Single Hop Detection with Clonal Selection Algorithm in Mobile Wireless Sensor Networks by L. S. Sindhuja, G. Padmavathi

    Published 2016-01-01
    “…These methods incur control overheads and the detection accuracy is low when the replica is selected as a witness node. …”
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  18. 118
  19. 119

    FB-YOLOv8s: A fire detection algorithm based on YOLOv8s by Yuhang Liu, Chunjuan Bo, Chong Feng

    Published 2025-01-01
    “…However, there exist some problems in traditional detection algorithms of fire, such as low accuracy, high miss rate, and low detection rate of small targets. …”
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  20. 120

    An Infrared Small Target Detection Algorithm Utilizing Joint Local Contrast Measure by Qing Zhao, Jiawen Liao, Derui Zhang

    Published 2025-01-01
    “…However, when dealing with complex backgrounds or targets close to the edges of jamming objects, existing algorithms typically encounter significant challenges, such as high false alarm rates and low detection probabilities. …”
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    Article