Showing 161 - 180 results of 1,810 for search '(( resources detection function ) OR (( source OR sources) detection function ))', query time: 0.20s Refine Results
  1. 161

    Dual‐Function Ceramic Pigments for Energy‐Efficient and Secure Autonomous Vehicles by Ik Hoon Jeong, Yong‐Jun Seo, Jum Soo Hwang, Geun Hyeong Kim, Yeong Jae Kim, Gil Ju Lee

    Published 2025-07-01
    “…The results indicate that although the scattering is not strictly retro‐reflective, it strongly redirects the incident wave back toward its source, which is advantageous for LiDAR‐based object detection. …”
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  2. 162

    YOLOGX: an improved forest fire detection algorithm based on YOLOv8 by Caixiong Li, Yue Du, Xing Zhang, Peng Wu

    Published 2025-01-01
    “…To tackle issues, including environmental sensitivity, inadequate fire source recognition, and inefficient feature extraction in existing forest fire detection algorithms, we developed a high-precision algorithm, YOLOGX. …”
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  3. 163
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  5. 165

    An Attomolar-Level Optical Device for Monitoring Receptor–Analyte Interactions Without Functionalization Steps: A Case Study of Cytokine Detection by Nunzio Cennamo, Francesco Arcadio, Chiara Marzano, Rosalba Pitruzzella, Mimimorena Seggio, Maria Pesavento, Stefano Toldo, Antonio Abbate, Luigi Zeni

    Published 2025-02-01
    “…The POF-based device was proven to be effective for detecting several interleukins at the attomolar level in a few minutes and without functionalization processes.…”
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  6. 166

    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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  7. 167

    MTAHG and MTBHG: Modified Approaches for Interpreting Gravity Data by Hazel Deniz Toktay, Hanbing Ai, Ahmad Alvandi, Kejia Su, Jinlei Li

    Published 2025-04-01
    “…This paper proposes two effective edge detection tools: one combining the balanced total horizontal gradient (BHG), and the hyperbolic tangent function, abbreviated as “MTBHG”; and the other combining the tilt angle of the total horizontal gradient (TAHG) and the hyperbolic tangent function, abbreviated as “MTAHG.” …”
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  8. 168
  9. 169

    ContDataQC: An R package and Shiny app for quality control of continuous water quality sensor data by Michael J. Pennino, Jen Stamp, Erik W. Leppo, David A. Gibbs, Britta G. Bierwagen

    Published 2025-05-01
    “…ContDataQC helps users speed up and standardize the QC process, minimize undetected data errors, and make full use of their sensor data. It has three main functions: generate QC reports to detect anomalies and erroneous data values, merge QC'd data files from different time periods, and generate time series plots and basic summary statistics. …”
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  10. 170
  11. 171

    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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  12. 172

    Functional and Genomic Evidence of L-Arginine-Dependent Bacterial Nitric Oxide Synthase Activity in <i>Paenibacillus nitricinens</i> sp. nov. by Diego Saavedra-Tralma, Alexis Gaete, Carolina Merino-Guzmán, Maribel Parada-Ibáñez, Francisco Nájera-de Ferrari, Ignacio Jofré-Fernández

    Published 2025-06-01
    “…Consequently, <i>P. nitricinens</i> expands the known repertoire of microbial NO synthesis and suggests a previously overlooked source of NO flux in well-aerated soils.…”
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  13. 173

    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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  14. 174

    Non-Line-of-Sight Location With Gauss Filtering Algorithm Based on a Model of Photon Flight by Yu Ren, Zongliang Xie, Yihan Luo, Shaoxiong Xu, Haotong Ma, Yi Tan

    Published 2020-01-01
    “…Recently, non-line-of-sight (NLOS) detection based on time of flight (TOF) has been investigated. …”
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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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    Spin-dependent edge detection and imaging enabled by optical circularly polarised states by Jiale Chen, Zhao-xian Chen, Zi-xin Zhou, Yan-qing Lu, Jun-long Kou

    Published 2025-04-01
    “…Furthermore, these two independent functions can be easily switched by altering the circular polarisation state of the light source.…”
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  20. 180

    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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