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  1. 81
  2. 82

    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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    Article
  3. 83

    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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  4. 84
  5. 85

    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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    Article
  6. 86

    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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  7. 87
  8. 88

    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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  9. 89

    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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    Article
  10. 90

    Millimeter-Wave Imaging with Range-Resolved 3D Depth Extraction Using Glow Discharge Detection and Frequency-Modulated Continuous Wave Radar by Arun Ramachandra Kurup, Daniel Rozban, Amir Abramovich, Yitzhak Yitzhaky, Natan Kopeika

    Published 2025-02-01
    “…Reflected signals are processed by the GDD, which functions as a heterodyne receiver, and Fast Fourier Transform (FFT) is used to extract range data. …”
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    Article
  11. 91

    Loss Function Optimization Method and Unsupervised Extraction Approach D-DBSCAN for Improving the Moving Target Perception of 3D Imaging Sonar by Jingfeng Yu, Aigen Huang, Zhongju Sun, Rui Huang, Gao Huang, Qianchuan Zhao

    Published 2025-03-01
    “…Compared to 2D sonar images, 3D sonar images offer superior spatial positioning capabilities, although the data acquisition cost is higher and lacks open source references for data annotation, target detection, and semantic segmentation. …”
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    Article
  12. 92

    Image Deconvolution to Resolve Astronomical X-Ray Sources in Close Proximity: The <i>NuSTAR</i> Images of SXP 15.3 and SXP 305 by Sayantan Bhattacharya, Dimitris M. Christodoulou, Silas G. T. Laycock

    Published 2025-03-01
    “…The broad point spread function of the <i>NuSTAR</i> telescope makes resolving astronomical X-ray sources a challenging task, especially for off-axis observations. …”
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  13. 93
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  15. 95

    KronNet a lightweight Kronecker enhanced feed forward neural network for efficient IoT intrusion detection by Saeed Ullah, Junsheng Wu, Mian Muhammad Kamal, Abdul Khader Jilani Saudagar

    Published 2025-07-01
    “…Abstract The rapid expansion of Internet of Things (IoT) networks necessitates efficient intrusion detection systems (IDS) capable of operating within the stringent resource constraints of IoT devices. …”
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  16. 96
  17. 97

    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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  18. 98

    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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  19. 99

    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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  20. 100

    Fine-grained building function recognition with street-view images and GIS map data via geometry-aware semi-supervised learning by Weijia Li, Jinhua Yu, Dairong Chen, Yi Lin, Runmin Dong, Xiang Zhang, Conghui He, Haohuan Fu

    Published 2025-03-01
    “…In this work, we propose a geometry-aware semi-supervised method for fine-grained building function recognition, which effectively uses multi-source geoinformation data to achieve accurate function recognition in both single-city and cross-city scenarios. …”
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