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Showing 441 - 460 results of 2,295 for search '((\ sources selection function\ ) OR (( resource OR resourcess) detection functions\ ))', query time: 0.28s Refine Results
  1. 441

    From fish to fiber: 3D-nanoprinted optical neuromast for multi-integrated underwater detection by Liangye Li, Xuhao Fan, Geng Chen, Yueqi Liu, Fujun Zhang, Zhuolin Chen, Zhi Zhang, Wangyang Xu, Shixiong Zhang, Yuncheng Liu, Zongjing Li, Hui Gao, Zhijun Yan, Wei Xiong, Qizhen Sun

    Published 2025-08-01
    “…Abstract Fish possess high sensitivity to acoustic, vibrational, and hydrodynamic stimuli through unique sensing cells, providing unparalleled paradigms for developing underwater detection methods. However, artificial perception devices face challenges in replicating comparable sensitivity and multi-dimensional integration of fish in function and scale. …”
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    Enhancing Human Detection in Occlusion-Heavy Disaster Scenarios: A Visibility-Enhanced DINO (VE-DINO) Model with Reassembled Occlusion Dataset by Zi-An Zhao, Shidan Wang, Min-Xin Chen, Ye-Jiao Mao, Andy Chi-Ho Chan, Derek Ka-Hei Lai, Duo Wai-Chi Wong, James Chung-Wai Cheung

    Published 2025-01-01
    “…VE-DINO enhances detection accuracy by incorporating body part key point information and employing a specialized loss function. …”
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  5. 445

    Lightweight coal miners and manned vehicles detection model based on deep learning and model compression techniques: A case study of coal mines in Guizhou region by Beijing XIE, Heng LI, Zheng LUAN, Zhen LEI, Xiaoxu LI, Zhuo LI

    Published 2025-02-01
    “…Compared to various lightweight architectures and advanced detection models, this method demonstrates excellent accuracy, lower computational costs, and better real-time performance, providing a feasible coal mine pedestrian-vehicle detection method for resource-constrained coal mine scenarios, meeting the deployment requirements of coal mine video surveillance and enabling real-time alerts for intelligent inspection of coal mine pedestrian-vehicles.…”
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  6. 446

    Securing Wireless Communications with Energy Harvesting and Multi-antenna Diversity by Nguyen Quang Sang, tran Cong Hung, tran Trung Duy, minh Tran, byung Seo Kim

    Published 2025-04-01
    “…Analytical expressions for the Signal-to-Noise Ratios (SNRs) at both the destination D and the eavesdropper E are derived, along with the Probability Density Function (PDF) and Cumulative Distribution Function (CDF) of these SNRs under block Rayleigh fading conditions. …”
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  7. 447

    Uncovering functional deterioration in the rhizosphere microbiome associated with post-green revolution wheat cultivars by Monique E. Smith, Vanessa N. Kavamura, David Hughes, Rodrigo Mendes, George Lund, Ian Clark, Tim H. Mauchline

    Published 2025-06-01
    “…Of the 113 functional genes that were differentially abundant between heritage and modern cultivars, 95% were depleted in modern cultivars and 65% of differentially abundant reads best mapped to genes involved in staurosporine biosynthesis (antibiotic product), plant cell wall degradation (microbial mediation of plant root architecture, overwintering energy source for microbes) and sphingolipid metabolism (signal bioactive molecules). …”
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  8. 448

    IMPLEMENTATION OF LEARNING MANAGEMENT SYSTEMS WITH GENERATIVE ARTIFICIAL INTELLIGENCE FUNCTIONS IN THE POST-PANDEMIC ENVIRONMENT by Denis-Cătălin Arghir

    Published 2024-04-01
    “…The system goes beyond traditional LMS functionalities by providing suggestions to enhance and diversify lessons. …”
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  9. 449

    Antimicrobial Activity of Chitosan from Different Sources Against Non-<i>Saccharomyces</i> Wine Yeasts as a Tool for Producing Low-Sulphite Wine by Francesco Tedesco, Rocchina Pietrafesa, Gabriella Siesto, Carmen Scieuzo, Rosanna Salvia, Patrizia Falabella, Angela Capece

    Published 2024-10-01
    “…Finally, the efficiency of different antimicrobial treatments was evaluated during laboratory-scale fermentations inoculated with a selected <i>S. cerevisiae</i> strain. The tested strains exhibited medium/high resistance to the chitosan; in some cases, the behaviour varied in the function of species/strain, and only four strains exhibited different resistance levels, depending on the chitosan source. …”
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    DECISION TREE WITH HILL CLIMBING ALGORITHM BASED SPECTRUM HOLE DETECTION IN COGNITIVE RADIO NETWORK by N Suganthi, R Meenakshi, A Sairam, M Parvathi

    Published 2025-06-01
    “…The approach integrates a Decision Tree (DT) algorithm for rapid initial classification of Primary User (PU) activity, followed by a Hill Climbing (HC) optimization algorithm that fine-tunes the detection based on a fitness function. Entropy and throughput metrics are employed as decision conditions at each sensing channel, enhancing uncertainty measurement and maintaining detection robustness under low Signal-to-Noise Ratio (SNR) conditions. …”
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  14. 454

    TCE-YOLOv5: Lightweight Automatic Driving Object Detection Algorithm Based on YOLOv5 by Han Wang, Zhenwei Yang, Qiaoshou Liu, Qiang Zhang, Honggang Wang

    Published 2025-05-01
    “…Finally, the EIOU loss function is introduced to measure the overlap between the predicted box and the real box more accurately and improve the detection accuracy. …”
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    YOLOv8n-DDSW: an efficient fish target detection network for dense underwater scenes by Jinwang Yi, Wei Han, Fangfei Lai

    Published 2025-04-01
    “…Therefore, the YOLOv8n-DDSW fish target detection algorithm was proposed in this article to resolve the detection difficulties resulting from fish occlusion, deformation and detail loss in complex intensive aquaculture scenarios. (1) The C2f-deformable convolutional network (DCN) module is proposed to take the place of the C2f module in the YOLOv8n backbone to raise the detection accuracy of irregular fish targets. (2) The dual-pooling squeeze-and-excitation (DPSE) attention mechanism is put forward and integrated into the YOLOv8n neck network to reinforce the features of the visible parts of the occluded fish target. (3) Small detection is introduced to make the network more capable of sensing small targets and improving recall. (4) Wise intersection over union (IOU) rather than the original loss function is used for improving the bounding box regression performance of the network. …”
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    Estimating Leaf Chlorophyll Fluorescence Parameters Using Partial Least Squares Regression with Fractional-Order Derivative Spectra and Effective Feature Selection by Jie Zhuang, Quan Wang

    Published 2025-02-01
    “…Chlorophyll fluorescence (ChlF) parameters serve as non-destructive indicators of vegetation photosynthetic function and are widely used as key input parameters in photosynthesis–fluorescence models. …”
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