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Showing 201 - 220 results of 1,810 for search '((( resource OR resource) detection function ) OR ( source detection function ))', query time: 0.33s Refine Results
  1. 201

    High-Quality and Enhanced-Resolution Single-Pixel Imaging Based on Spiral Line Array Laser Source by Guozhong Lei, Haolong Jia, Wenchang Lai, Wenhui Wang, Wenda Cui, Yan Wang, Hao Liu, Kai Han

    Published 2024-01-01
    “…We propose a spiral line array laser source which can generate random illumination light fields without periodicity in the normalized second-order correlation function <italic>g</italic><sup>(2)</sup>. …”
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    Bias‐Independent True Random Number Generator Circuit using Memristor Noise Signals as Entropy Source by Jinwoo Park, Hyunjoong Kim, Hyungjin Kim

    Published 2025-06-01
    “…Finally, the performance of the designed TRNG circuit is evaluated using autocorrelation functions and National Institute of Standards and Technology tests, confirming its capability to produce random number bitstreams.…”
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  6. 206

    Varying Activity and the Burst Properties of FRB 20240114A Probed with GMRT Down to 300 MHz by Ajay Kumar, Yogesh Maan, Yash Bhusare

    Published 2024-01-01
    “…All of the bursts we detect are faint (<10 Jy ms) and thus probe the lower end of the energy distribution. …”
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  7. 207

    Potential Source Regions and Transportation Pathways of Reactive Gases at a Regional Background Site in Northwestern China by Quanwei Zhao, Qing He, Lili Jin, Jianlin Wang

    Published 2021-01-01
    “…Wind rose, cluster analysis, potential source contribution function (PSCF), and concentration-weighted trajectory (CWT) methods were adopted for identifying the transport pathways and potential source regions of these atmosphere components at Akedala. …”
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  8. 208

    DWS-YOLO: A Lightweight Detector for Blood Cell Detection by Yihai Mao, Hongyi Zhang, Wanqing Wu, Xingen Gao, Zhibin Lin, Juqiang Lin

    Published 2024-12-01
    “…Improved attention, loss function, and suppression enhance detection accuracy, while lightweight C3 module reduces computation time. …”
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    Article
  9. 209

    Research on intrusion detection model based on improved MLP algorithm by Qihao Zhao, Fuwei Wang, Weimin Wang, Tianxin Zhang, Haodong Wu, Weijun Ning

    Published 2025-02-01
    “…These patterns can be effectively captured through MLP’s multiple nonlinear transformations, such as ReLU and Sigmoid activation functions, which are especially beneficial for intrusion detection. …”
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    Randomization-Driven Hybrid Deep Learning for Diabetic Retinopathy Detection by A. M. Mutawa, G. R. Hemalakshmi, N. B. Prakash, M. Murugappan

    Published 2025-01-01
    “…This study pioneers an innovative framework, using Multi-Scale Discriminative Robust Local Binary Pattern (MS-DRLBP) features, combined with a hybrid Convolutional Neural Network-Radial Basis Function (CNN-RBF) classifier, to enhance the detection of DR. …”
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    Algorithms for Automatic Detection and Location of Infrasound Events in the PSDL System by Asming Vladimir Ernestovich, Fedorov Andrey Viktorovich

    Published 2024-12-01
    “…An algorithm for detecting infrasound signals by calculating the cross-correlation function between records of individual sensors in a array is described. …”
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    Article
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    Lightweight Detection Algorithm for Breast-Mass Features in Ultrasound Images by Taojuan Li, Wen Liu, Mingxian Song, Zheng Gu, Ling Hai

    Published 2025-01-01
    “…Thus, the proposed model effectively balances detection performance and lightweight design, making it well-suited for real-time applications on resource-constrained computing devices.…”
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  16. 216

    A lightweight personnel detection method for underground coal mines by Shuai WANG, Wei YANG, Yuxiang LI, Jiaqi WU, Wei YANG

    Published 2025-04-01
    “…Introduce SIoU instead of the original loss function to accelerate model convergence. Finally, the introduction of the Ghost module to optimize the backbone network can reduce the computational and parametric quantities of the model without losing the model performance, improve the detection speed, and make the model easier to be deployed on resource-constrained devices. …”
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  17. 217

    Code vulnerability detection method based on graph neural network by Hao CHEN, Ping YI

    Published 2021-06-01
    “…The schemes of using neural networks for vulnerability detection are mostly based on traditional natural language processing ideas, processing the code as array samples and ignoring the structural features in the code, which may omit possible vulnerabilities.A code vulnerability detection method based on graph neural network was proposed, which realized function-level code vulnerability detection through the control flow graph feature of the intermediate language.Firstly, the source code was compiled into an intermediate representation, and then the control flow graph containing structural information was extracted.At the same time, the word vector embedding algorithm was used to initialize the vector of basic block to extract the code semantic information.Then both of above were spliced to generate the graph structure sample data.The multilayer graph neural network model was trained and tested on graph structure data features.The open source vulnerability sample data set was used to generate test data to evaluate the method proposed.The results show that the method effectively improves the vulnerability detection ability.…”
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  18. 218

    Detection of water surface targets based on improved Deformable DETR by Pengjiu WANG, Junbin Gong, Wei LUO, Xiao HUANG, Junjie GUO

    Published 2025-06-01
    “…Objective With technological advancements and the increasing demand for water resource exploration, water surface target detection plays a crucial role in various applications, such as ship navigation and maritime safety. …”
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    A Benchmark Review of YOLO Algorithm Developments for Object Detection by Zhengmao Hua, Kaviya Aranganadin, Cheng-Cheng Yeh, Xinhe Hai, Chen-Yun Huang, Tsan-Chuen Leung, Hua-Yi Hsu, Yung-Chiang Lan, Ming-Chieh Lin

    Published 2025-01-01
    “…You Only Look Once (YOLO) has established itself as a prominent object detection framework due to its excellent balance between speed and accuracy. …”
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    Article