Showing 181 - 200 results of 1,810 for search '(( resource detection functions ) OR (( source OR sources) detection function ))', query time: 0.44s Refine Results
  1. 181

    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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  4. 184

    QPPLab: A generally applicable software package for detecting, analyzing, and visualizing large-scale quasiperiodic spatiotemporal patterns (QPPs) of brain activity by Nan Xu, Behnaz Yousefi, Nmachi Anumba, Theodore J. LaGrow, Xiaodi Zhang, Shella Keilholz

    Published 2025-02-01
    “…To address these challenges, we present QPPLab, an open-source MATLAB-based toolbox for detecting, analyzing, and visualizing QPPs from fMRI time series. …”
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  5. 185

    Neural network for step anomaly detection in head motion during fMRI using meta-learning adaptation by N.S. Davydov, V.V. Evdokimova, P.G. Serafimovich, V.I. Protsenko, A.G. Khramov, A.V. Nikonorov

    Published 2023-12-01
    “…Quality assessment and artifact detection in functional magnetic resonance imaging (fMRI) data is essential for clinical applications and brain research. …”
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  6. 186

    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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  7. 187

    Western spotted skunk spatial ecology in the temperate rainforests of the Pacific Northwest by Marie I. Tosa, Damon B. Lesmeister, Taal Levi

    Published 2024-08-01
    “…Using these home ranges, we fitted a resource selection function using environmental covariates that we assigned to various hypotheses such as resources, predator avoidance, thermal tolerance, and disturbance. …”
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  8. 188

    Urban Traffic State Sensing and Analysis Based on ETC Data: A Survey by Yizhe Wang, Ruifa Luo, Xiaoguang Yang

    Published 2025-06-01
    “…The construction of multi-source data fusion frameworks enables effective complementarity between ETC data, floating car data, and video detection data, significantly improving traffic state estimation accuracy. …”
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    Development of an embedded diagnostic tool for visual misalignment screening by Daniel Soto Rodriguez, Andres Eduardo Rivera Gomez, Ruthber Rodriguez Serrezuela

    Published 2025-09-01
    “…A novel treatment validation mechanism was implemented by analyzing pupil-to-stimulus distance frame-by-frame, confirming reliable eye tracking and the system’s potential for detecting microstrabismus. This open-source, portable prototype is suitable for community health screening and educational use, particularly in low-resource settings.…”
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  12. 192

    SDES-YOLO: A high-precision and lightweight model for fall detection in complex environments by Xiangqian Huang, Xiaoming Li, Limengzi Yuan, Zhao Jiang, Hongwei Jin, Wanghao Wu, Ru Cai, Meilian Zheng, Hongpeng Bai

    Published 2025-01-01
    “…These results indicate that SDES-YOLO successfully combines efficiency and precision in fall detection. Through these innovations, SDES-YOLO not only improves detection accuracy but also optimizes computational efficiency, making it effective even in resource-constrained environments.…”
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  13. 193

    Reinforcement Q-Learning-Based Adaptive Encryption Model for Cyberthreat Mitigation in Wireless Sensor Networks by Sreeja Balachandran Nair Premakumari, Gopikrishnan Sundaram, Marco Rivera, Patrick Wheeler, Ricardo E. Pérez Guzmán

    Published 2025-03-01
    “…The proposed model leverages a deep learning-based anomaly detection system to classify network states into low, moderate, or high threat levels, which guides encryption policy selection. …”
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  14. 194

    Nitrate Nitrogen Quantification via Ultraviolet Absorbance: A Case Study in Agricultural and Horticultural Regions in Central China by Yiheng Zang, Jing Chen, Muhammad Awais, Mukhtar Iderawumi Abdulraheem, Moshood Abiodun Yusuff, Kuan Geng, Yongqi Chen, Yani Xiong, Linze Li, Yanyan Zhang, Vijaya Raghavan, Jiandong Hu, Junfeng Wu, Guoqing Zhao

    Published 2025-05-01
    “…Soil nitrate nitrogen (NO<sub>3</sub><sup>−</sup>-N) is a key indicator of agricultural non-point source pollution. The ultraviolet (UV) dual-wavelength method is widely used for NO<sub>3</sub><sup>−</sup>-N detection, but interference from complex soil organic matter affects its accuracy. …”
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    Productivity, activity of digestive and antioxidant enzymes of carp (Cyprinus carpio Linnaeus, 1758) as a result of the use of inulin in low-nutrient feeds by O. Deren, O. Dobrianska, M. Koryliak

    Published 2025-06-01
    “…The practical use of the knowledge gained outlines the possibility of optimizing the production of fish when introducing resource-saving technologies in aquaculture.…”
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    Research on Interference Resource Optimization Based on Improved Whale Optimization Algorithm by Xuyi Chen, Mingxi Ma, Chengkui Liu, Haifeng Xie, Shaoqi Wang

    Published 2025-01-01
    “…In this problem, this paper establishes an interference resource optimization model with radar detection probability, interference effectiveness, and interference bandwidth utilization as the objective functions. …”
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  19. 199

    A review on WSN based resource constrained smart IoT systems by Shreeram Hudda, K. Haribabu

    Published 2025-05-01
    “…DL), D2D communication, Computer Vision, and Network Function Virtualization (i.e. NFV). Additionally, it emphasizes assessing and offloading specific IoT application functions onto the network’s edge to enhance performance. …”
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  20. 200

    Rice Disease Detection: TLI-YOLO Innovative Approach for Enhanced Detection and Mobile Compatibility by Zhuqi Li, Wangyu Wu, Bingcai Wei, Hao Li, Jingbo Zhan, Songtao Deng, Jian Wang

    Published 2025-04-01
    “…This study aims to develop a rice disease detection model that is highly accurate, resource efficient, and suitable for mobile deployment to address the limitations of existing technologies. …”
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