Showing 21 - 40 results of 993 for search 'Resources detection function', query time: 0.21s Refine Results
  1. 21

    A near-optimal resource allocation strategy for minimizing the worse-case impact of malicious attacks on cloud networks by Yu-Fang Chen, Frank Yeong-Sung Lin, Kuang-Yen Tai, Chiu-Han Hsiao, Wei-Hsin Wang, Ming-Chi Tsai, Tzu-Lung Sun

    Published 2025-08-01
    “…The proposed model integrates Virtual Machine (VM) initiation decisions and employs the Contest Success Function (CSF) within a two-player max–min game framework to dynamically allocate resources. …”
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  2. 22

    Research Progress on Dual Function Radar and Communication Signal Design and its Application in Typical Detection Scenarios by Yaping HE, Longfei SHI, Dong WANG, Jianglan TANG, Junxian CHEN, Jiazhi MA, Jialei LIU

    Published 2025-08-01
    “…Dual Function Radar and Communication (DFRC)-integrated electronic equipment platform, which combines detection and communication functions, effectively addresses issues such as platform limitations, resource constraints, and electromagnetic compatibility by sharing hardware platforms and transmitting waveforms. …”
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  3. 23

    LFN-YOLO: precision underwater small object detection via a lightweight reparameterized approach by Mingxin Liu, Mingxin Liu, Yujie Wu, Ruixin Li, Cong Lin, Cong Lin

    Published 2025-01-01
    “…Underwater object detection plays a significant role in fisheries resource assessment and ecological environment protection. …”
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    Vehicle detection method based on multi-layer selective feature for UAV aerial images by Yinbao Ma, Yuyu Meng, Jiuyuan Huo

    Published 2025-07-01
    “…For the detection head, a Generalized Wasserstein Distance Loss (GWDLoss) function is proposed to quantify positional and scale discrepancies, improving the adaptability of bounding box regression to geometric variations. …”
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  7. 27

    DRBD-YOLOv8: A Lightweight and Efficient Anti-UAV Detection Model by Panpan Jiang, Xiaohua Yang, Yaping Wan, Tiejun Zeng, Mingxing Nie, Zhenghai Liu

    Published 2024-11-01
    “…Achieving real-time detection with high accuracy, while accommodating the limited resources of edge-computing devices poses a significant challenge for anti-UAV detection. …”
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    Metal surface defect detection using SLF-YOLO enhanced YOLOv8 model by Yuan Liu, Yilong Liu, Xiaoyan Guo, Xi Ling, Qingyi Geng

    Published 2025-04-01
    “…Abstract This paper addresses the industrial demand for precision and efficiency in metal surface defect detection by proposing SLF-YOLO, a lightweight object detection model designed for resource-constrained environments. …”
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    An Optimized FPGA-Based FDIR System for Sensor Fault Detection in Satellite Attitude Estimation by Xianliang Chen, Zhicheng Xie, Jiashu Wu, Xiaofeng Wu

    Published 2025-01-01
    “…To solve this problem, a Fault Detection, Isolation, and Recovery (FDIR) was proposed, which integrates an adaptive unscented Kalman filter (AUKF), a radial basis function (RBF) neural network for fault detection, and a QUEST-based estimator. …”
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    Design and Validation of a Lightweight Entropy-Based Intrusion Detection Algorithm for Automotive CANs by Jiacheng Chen, Zhifu Wang

    Published 2025-06-01
    “…Experimental results demonstrate robust performance under low computational resources, achieving high detection accuracy with high recall (>80%) even at 10% bus load fluctuation thresholds. …”
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  17. 37

    YOLOv11-GSF: an optimized deep learning model for strawberry ripeness detection in agriculture by Haoran Ma, Qian Zhao, Runqing Zhang, Chunxu Hao, Wenhui Dong, Xiaoying Zhang, Fuzhong Li, Xiaoqin Xue, Gongqing Sun

    Published 2025-08-01
    “…To overcome these limitations, this paper introduces YOLOv11-GSF, a real-time strawberry ripeness detection algorithm based on YOLOv11, which incorporates several innovative features: a Ghost Convolution (GhostConv) convolution method for generating rich feature maps through lightweight linear transformations, thereby reducing computational overhead and enhancing resource utilization; a C3K2-SG module that combines self-moving point convolution (SMPConv) and convolutional gated linear units (CGLU) to better capture the local features of strawberry ripeness; and a F-PIoUv2 loss function inspired by Focaler IoU and PIoUv2, utilizing adaptive penalty factors and interval mapping to expedite model convergence and optimize ripeness classification. …”
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    Analysis of Facial Cues for Cognitive Decline Detection Using In-the-Wild Data by Fatimah Alzahrani, Steve Maddock, Heidi Christensen

    Published 2025-06-01
    “…Video-based analysis offers a promising, low-cost alternative to resource-intensive clinical assessments. This paper investigates visual features (eye blink rate (EBR), head turn rate (HTR), and head movement statistical features (HMSFs)) for distinguishing between neurodegenerative disorders (NDs), mild cognitive impairment (MCI), functional memory disorders (FMDs), and healthy controls (HCs). …”
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