Showing 701 - 720 results of 2,109 for search 'low detection algorithm', query time: 0.13s Refine Results
  1. 701
  2. 702

    Multiradar Collaborative Task Scheduling Algorithm Based on Graph Neural Networks with Model Knowledge Embedding by Haoqing LI, Dian YU, Changchun PAN, Wenxian YU, Dongying LI

    Published 2025-04-01
    “…This method frames the radar task collaborative scheduling problem as a heterogeneous network graph, leveraging model knowledge to optimize the training process of the Graph Neural Network (GNN) algorithm. A key innovation of this algorithm is its capability to capture critical model knowledge using low-complexity calculations, which helps to further optimize the GNN model. …”
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  3. 703

    DCE-YOLOv8: Lightweight and Accurate Object Detection for Drone Vision by Jinsu An, Dong Hee Lee, Muhamad Dwisnanto Putro, Byeong Woo Kim

    Published 2024-01-01
    “…DCE-YOLOv8 is engineered to address the low detection rate of small objects in drone imagery. …”
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  4. 704

    Machine vision-based detection of key traits in shiitake mushroom caps by Jiuxiao Zhao, Jiuxiao Zhao, Wengang Zheng, Wengang Zheng, Yibo Wei, Yibo Wei, Qian Zhao, Qian Zhao, Jing Dong, Jing Dong, Xin Zhang, Xin Zhang, Mingfei Wang, Mingfei Wang

    Published 2025-02-01
    “…Finally,M3 group using GWO_SVM algorithm achieved optimal performance among six mainstream machine learning models tested with an R²value of 0.97 and RMSE only at 0.038 when comparing predicted values with true values. …”
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  5. 705

    High-Throughput cDNA Screening Utilizing a Low Order Neural Network Filter by Guyang Matthew Huang, James Farkas, Leroy Hood

    Published 1996-12-01
    “…The filter was applied to a library of 2123 anonymous cDNA sequences, which resulted in 61 detections. Evaluation of the detections with two other dissimilar computer prediction algorithms yielded strong transmembrane predictions for 15 of the detections, while 8 of the detections resulted in a definitive negative result. …”
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  6. 706

    Infrared dim tiny-sized target detection based on feature fusion by Peng Zhang, Yaman Jing, Guodong Liu, Ziyang Chen, Xiaoyan Wu, Osami Sasaki, Jixiong Pu

    Published 2025-02-01
    “…In certain instances, such as when the infrared target is situated at a considerable distance from the detector, the detected object exhibits diminutive dimensions with a concurrently low signal intensity, leading to a challenge in achieving precision in object detection. …”
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  7. 707

    Optimized DINO model for accurate object detection of sesame seedlings and weeds by Yong Wang, ShunFa Xu, ZhenYuan Ye, KongHao Cheng

    Published 2025-04-01
    “…However, in environments where the target and the surrounding morphology are highly similar, such as distinguishing sesame seedlings from weeds, the problem essentially becomes one of optimizing edge detection algorithms for similar targets. To address this issue in agricultural object detection, we developed a custom dataset containing 1,300 images of sesame seedlings and weeds. …”
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  8. 708

    Hybridization of Cognitive Radar and Phased Array Radar Having Low Probability of Intercept Transmit Beamforming by Abdul Basit, Ijaz Mansoor Qureshi, Wasim Khan, Ihsan Ulhaq, Shafqat Ullah Khan

    Published 2014-01-01
    “…Hence, the PAR high gain scanned beam patterns, over the entire surveillance region, are spoiled to get the series of low gain basis patterns. For unaffected array detection performance, these basis patterns are linearly combined to synthesize the high gain beam pattern in the desired direction using the set of weight. …”
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  9. 709

    DOPPLER SPECTRUM MATHEMATICAL MODEL OF SIGNAL SCATTERING FROM SEA SURFACE AT LOW GRAZING ANGLES by Mikhail A. Borodin, Vyacheslav N. Mikhaylov, Polina A. Filippova

    Published 2019-07-01
    “…The developed mathematical model is offered to use for the design of algorithm sea surface condition estimation and pollutant detection using the signal which received by radar.…”
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  10. 710
  11. 711

    A Distributed Low-Degree-of-Freedom Aerial Target Localization Method Based on Hybrid Measurements by Xiaoshuang Jiao, Jinming Chen, Lifeng Jiang, Weiping Li, Xiaochao Yang, Weiwei Wang, Jun Zhang

    Published 2025-05-01
    “…For real-time detection scenarios such as battlefield reconnaissance and surveillance, where high positioning accuracy is required and receiving station resources are limited, we propose an innovative distributed aerial target localization method with low degrees of freedom. …”
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  12. 712

    A new Digital Harmony Search algorithm for optimizing Pump Scheduling in Water Distribution Networks by Francesco De Paola, Francesco Pugliese, Nicola Fontana, Maurizio Giugni

    Published 2025-05-01
    “…Pumps in Water Distribution Networks (WDNs) adequately provide effective pressure where low elevation or high head losses are detected within the system. …”
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  13. 713

    Improvements from incorporating machine learning algorithms into near real-time operational post-processing by Gabrielle Tepp, Ellen Yu, Aparna Bhaskaran, Ryan Tam, Weiqiang Zhu, Zackary Newman, Erika Jaski, Nick Scheckel

    Published 2025-08-01
    “…ST-Proc uses PhaseNet to find phase picks and the machine learning algorithm GaMMA to associate events. This pipeline is capable of correctly detecting events in 65–70% of triggers containing events with a low false event rate around 5%. …”
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  14. 714

    Optimizing Bi-LSTM networks for improved lung cancer detection accuracy. by Su Diao, Yajie Wan, Danyi Huang, Shijia Huang, Touseef Sadiq, Mohammad Shahbaz Khan, Lal Hussain, Badr S Alkahtani, Tehseen Mazhar

    Published 2025-01-01
    “…We employed traditional hand-crafted features, such as Gray Level Co-occurrence Matrix (GLCM) features, in conjunction with traditional machine learning algorithms. To explore the potential of deep learning, we also optimized and implemented a Bidirectional Long Short-Term Memory (Bi-LSTM) network for lung cancer detection. …”
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  15. 715

    RQPool: A Novel Multi-Branch Graph-Level Anomaly Detection by Aaron Alex Philip, Ziad Kobti

    Published 2025-05-01
    “…Moreover, existing Graph Neural Network (GNN) algorithms focus primarily on spatial domain features while neglecting spectral properties. …”
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  16. 716

    Lightweight network for insulator fault detection based on improved YOLOv5 by Dehua Weng, Zhiliang Zhu, Zhengbing Yan, Moran Wu, Ziang Jiang, Nan Ye

    Published 2024-12-01
    “…To address these issues, we introduce a novel one-stage network that enables real-time detection of insulator faults on mobile devices. We designed a new module that optimises the computational complexity of networks and fused the module with the attention mechanism SimAM to solve the problem of low efficiency in detecting flashover faults. …”
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  17. 717

    Anomaly Detection in Network Traffic Using Advanced Machine Learning Techniques by Stephanie Ness, Vishwanath Eswarakrishnan, Harish Sridharan, Varun Shinde, Naga Venkata Prasad Janapareddy, Vineet Dhanawat

    Published 2025-01-01
    “…By comparing different algorithms, this research contributes to advancing the application of machine learning in network security, offering guidance on model selection and optimization for improved detection of cyber threats.…”
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  18. 718

    Distribution of urinary neutrophil gelatinase-associated lipocalin and post-translationally modified fetuin-A in outpatients with acute kidney disease detected using a nationwide a... by Ya-Chi Lin, I-Wen Ting, David Ray Chang, Ya-Luan Hsiao, Yu-Ting Lin, Mei-Chuan Hsieh, Shu-Woei Ju, Jie-Sian Wang, Chang-Cheng Jiang, Hsuan-Jen Lin, Cheng-Ting Lu, Che-Chen Lin, Tzu-Ling Tseng, Hung-Chieh Yeh, Hsiu-Yin Chiang, Chin-Chi Kuo

    Published 2025-07-01
    “…Conclusions: The high proportion of elevated uNGAL and its positive association with CKO risk provide biological evidence to support the AKIDS's data algorithm in detecting AKDOPT. Similarly, uPTM-FetA demonstrated comparable characteristics to uNGAL in reflecting kidney injury in the context of AKD.…”
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  19. 719

    Scene Text Detection and Recognition Using Maximally Stable Extremal Region by Golda Jeyasheeli P, Athinarayanan B, Manish T, Mohamad Umar M

    Published 2024-12-01
    “…Traditional text detection and recognition methods may struggle with detecting and recognizing text in images with low resolution, complex backgrounds, and varying font sizes. …”
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  20. 720