Small Defects Detection of Galvanized Strip Steel via Schatten-<i>p</i> Norm-Based Low-Rank Tensor Decomposition by Shiyang Zhou, Xuguo Yan, Huaiguang Liu, Caiyun Gong

“…It is a fundamental but “hard” small target detection problem due to its small pixel occupation in low-contrast images. …”
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Multi scale power spectral density subband gradient-based spectrum sensing algorithm and performance analysis by Yang ZHANG, Hua PENG, Ke-xian GONG

“…In addition, the proposed algorithm is robust for noise varia uncertainty, even in the low SNR environment.…”
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An efficient smoothing algorithm for range external guidance data based on dynamic threshold and adaptive interpolation by Shixue Zhang, Huihui Cai, Houfeng Wang, Shuai Liu, Qiang He

“…Experimental results demonstrate that the proposed dynamic threshold-based five-point extrapolation outlier elimination method achieves an average outlier detection rate of over 80% with a very low false alarm rate. …”
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An Obstacle Perception Algorithm Based on Multi-Sensor Fusion for Autonomous-Rail Rapid Transit by JIANG Liangyu, PAN Wenbo, HUANG Ruipeng

“…This paper presents an obstacle perception algorithm based on multi-sensor fusion, aimed at addressing omissions and errors, as well as low accuracy in object detection for autonomous-rail rapid transit (ART). …”
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Low sensitivity of the fourth‐generation antigen/antibody HIV rapid diagnostic test Determine™ HIV Early Detect for detection of acute HIV infection at the point of care in rural E... by Iza Ciglenecki, Nombuso Ntshalintshali, Esther Mukooza, Skinner Lekelem, Mpumelelo Mavimbela, Sindisiwe Dlamini, Lenhle Dube, Nomvuyo Mabuza, Melat Haile, Tom Ellman, Antonio Flores, Olivia Keiser, Sindy Matse, Roberto de laTour, Alexandra Calmy, Bernhard Kerschberger

“…Conclusions The low sensitivity of Determine™ HIV Early Detect to detect AHI when performed at the point of care using finger‐prick blood samples in our study contrasts with other published evaluations from laboratory settings and highlights the importance of field evaluations of the commonly used diagnostic tests.…”
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Protection and Security Method for Multiple Energy Power Plant-Based Microgrids Using Dual Filtering Algorithm by Danni Liu, Shengda Wang, Weijia Su, Xiaojuan Zhang, Shichun Hui

“…The main objective of this research is to design such protection and security schemes which detect, classify, and locate faults with high accuracy and rapidly with very low computational burden. …”
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Cautiously optimistic: paediatric critical care nurses’ perspectives on data-driven algorithms in low-resource settings—a human-centred design study in Malawi by Margot Rakers, Daniel Mwale, Lieke de Mare, Lezzie Chirambo, Bart Bierling, Alice Likumbo, Josephine Langton, IMPALA Study team, Niels Chavannes, Hendrikus van Os, Job Calis, Kiran Dellimore, María Villalobos-Quesada

“…Abstract Background Paediatric critical care nurses face challenges in promptly detecting patient deterioration and delivering high-quality care, especially in low-resource settings (LRS). …”
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Nonuniform Doppler extraction-enhanced multichannel extensive cancellation algorithm for passive radar using Iridium satellite signals by Hongwei Fu, Zhang Zhang, Yu Luo, Tingting Fu, Jianglin Li, Xin Jian, Hao Cha

“…In addition, to address the problem of multipath clutter broadening caused by the dual movement of low-orbit satellites and the PR receiver, this paper proposes a nonuniform Doppler extraction-enhanced multichannel extensive cancellation algorithm (NuDE-mECA) to suppress multipath clutter broadening while preserving near-field low-speed target detection capabilities. …”
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Low-Light Image and Video Enhancement for More Robust Computer Vision Tasks: A Review by Mpilo M. Tatana, Mohohlo S. Tsoeu, Rito C. Maswanganyi

“…Low-light enhancement (LLE) is crucial as computer vision tasks fail in the absence of sufficient lighting, having to rely on the addition of peripherals such as sensors. …”
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Low-power speech denoising method for non-stationary noise in underground mines by Yi YANG, Xiao TAN, Yajun CHANG, Keping WANG, Binbin LIU, Tian WANG

“…Especially when the signal-to-noise ratio is −5 dB, the algorithm proposed in this paper can still improve the segmented signal-to-noise ratio to −2.799 5 dB, indicating that the algorithm has strong denoising ability for ultra-low signal-to-noise ratio noisy speech. …”
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Himawari-8 satellite detection of morning terrain fog in a subtropical region by Huiyun Ma, Changjuan Chen, Zhicong Yi, Huihui Feng, Xiaojing Wu

“…This study explores the construction of a subtropical morning terrain fog detection algorithm for Himawari-8 data. Specifically, the clear sky surface suppression index is constructed to preliminarily remove the clear sky surface by combining Farneback optical flow method. …”
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Fault Detection in MV Switchgears Through Unsupervised Learning of Temperature Conditions by Grazia Iadarola, Alessandro Mingotti, Virginia Negri, Susanna Spinsante

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Driveway Detection for Weed Management in Cassava Plantation Fields in Thailand Using Ground Imagery Datasets and Deep Learning Models by Ithiphat Opasatian, Tofael Ahamed

“…In summary, image segmentation for detecting driveways can improve weed management in cassava fields, and the further automation of low-cost mechanical weeders in tropical climates can be performed based on the YOLACT algorithm.…”
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Adltformer Team-Training with Detr: Enhancing Cattle Detection in Non-Ideal Lighting Conditions Through Adaptive Image Enhancement by Zhiqiang Zheng, Mengbo Wang, Xiaoyu Zhao, Zhi Weng

“…This study proposes an image enhancement detection technique based on Adltformer (Adaptive dynamic learning transformer) team-training with Detr (Detection transformer) to improve model accuracy in suboptimal conditions, addressing the challenge of detecting cattle in real pastures under complex lighting conditions—including backlighting, non-uniform lighting, and low light. …”
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Research on pedestrian detection technology for mining unmanned vehicles by ZHOU Libing, YU Zhengqian, WEI Jianjian, JIANG Xueli, YE Baisong, ZHAO Yexin, YANG Siliang

“…To tackle issues of missed detections and low accuracy in pedestrian detection, an improved YOLOv3-based pedestrian detection algorithm for mining unmanned vehicles was introduced. …”
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Reduced-dose deep learning iterative reconstruction for abdominal computed tomography with low tube voltage and tube current by Shumeng Zhu, Baoping Zhang, Qian Tian, Ao Li, Zhe Liu, Wei Hou, Wenzhe Zhao, Xin Huang, Yao Xiao, Yiming Wang, Rui Wang, Yuhang Li, Jian Yang, Chao Jin

“…This study investigated the feasibility of a deep learning iterative reconstruction algorithm (Deep IR) in reducing the radiation dose while improving the image quality for abdominal computed tomography (CT) with low tube voltage and current. …”
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Non-destructive detection of early wheat germination via deep learning-optimized terahertz imaging by Guangming Li, Hongyi Ge, Yuying Jiang, Yuan Zhang, Xi Jin

“…However, current THz imaging techniques are limited by low image resolution, which restricts their practical application. …”
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Facilitating automated fact-checking: a machine learning based weighted ensemble technique for claim detection by Md. Rashadur Rahman, Rezaul Karim, Mohammad Shamsul Arefin, Pranab Kumar Dhar, Gahangir Hossain, Tetsuya Shimamura

“…To determine the optimal model and feature representation for claim detection, various machine learning algorithms were evaluated using BoW, TF-IDF, Word2Vec, and FastText features. …”
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A Segmented Low-Order Bistable Stochastic Resonance Method for Fixed-Distance Target Detection in Millimeter-Wave Fuze Under Rainy Conditions by Bing Yang, Kaiwei Wu, Zhe Guo, Yanbin Liang, Shijun Hao, Zhonghua Huang

“…To address these limitations while satisfying real-time processing requirements, this study proposes (1) a novel segmented low-order bistable stochastic resonance (SLOBSR) system based on piecewise polynomial potential functions and (2) a corresponding fixed-distance target detection algorithm incorporating signal pre-processing, particle swarm optimization (PSO)-based parameter optimization, and kurtosis threshold detection. …”
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Machine learning models and dimensionality reduction for improving the Android malware detection by Pablo Morán, Antonio Robles-Gómez, Andres Duque, Llanos Tobarra, Rafael Pastor-Vargas

“…They can detect an average of 91.72% malware samples, with a very low false positive rate of 0.13%, and using only 5,000 features. …”
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