Adaptive Robust Low-Beam Feature Point Detection Algorithm Based on Convex Hull by Qiqi Shen, Jie Wu

“…The existing algorithms for detecting low-beam feature points are neither universally applicable nor effective. …”
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Small target drone algorithm in low-altitude complex urban scenarios based on ESMS-YOLOv7 by Yuntao Wei, Xiujia Wang, Chunjuan Bo, Zhan Shi

“…Notably, there is a deficit in anti- UAV technologies for civilian use, particularly in complex urban environments at low altitudes. This paper proposes the ESMS-YOLOv7 algorithm, which is specifically engineered to detect small target UAVs in such challenging urban landscapes. …”
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A low complexity detection algorithm for large scale multiuser MIMO based on message passing by Qiong WANG, Wei YE, Mingming JI

“…According to the problem of high complexity of base station detection in large scale multiuser multiple input multiple output (MIMO) system,a low complexity multiuser variable node full information Gaussian message passing iterative detection algorithm based on forced convergence (VFI-GMPID-FC) was proposed.Firstly,the traditional Gaussian message passing iterative detection (GMPID) algorithm was improved to obtain VFI-GMPID algorithm,the detection performance of the VFI-GMPID algorithm approximates the minimum mean square error detection (MMSE) algorithm,but the complexity was considerably less than the MMSE algorithm.Then,the VFI-GMPID-FC algorithm was proposed to reduce the complexity of the algorithm and improve the detection efficiency.Finally,the simulation results show that the proposed algorithm can effectively reduce the algorithm complexity while ensuring the detection performance.…”
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Dark-YOLO: A Low-Light Object Detection Algorithm Integrating Multiple Attention Mechanisms by Ye Liu, Shixin Li, Liming Zhou, Haichen Liu, Zhiyu Li

“…To address these challenges, this paper proposes a low-light object detection algorithm named Dark-YOLO, which dynamically extracts features. …”
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A low-complexity AMP detection algorithm with deep neural network for massive mimo systems by Zufan Zhang, Yang Li, Xiaoqin Yan, Zonghua Ouyang

Subjects: “…Approximate message passing (AMP) detection algorithm…”
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YOLORM: An Advanced Key Point Detection Method for Accurate and Efficient Rotameter Reading in Low Flow Environments by Huang Yong, Xia Xing, Xiao Shengwang

“…Automatic reading of rotameters in low flow and challenging environments poses substantial accuracy and efficiency challenges. …”
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Low Voltage AC Series Arc Fault Detection Method Based on Approximate Entropy for Low Computational Performance Device by Kyoung-Tak Kim, Min-Ho Yoon, Chan-Muk Park, Joung-Hu Park, Sung-Hun Lim

“…This paper proposes an algorithm for detecting series arc faults in low-voltage AC residential environments. …”
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On-board Multi-User Detection Algorithm Based on Conditional Neural Process by Yilun LIU, Liang JIN, Jiali LI, Lidong ZHU

“…With the characteristics of all-terrain, all-weather and seamless coverage, satellite communications have become a potentially important part of 6G.An important prerequisite for achieving satellite intelligence is that the satellite have on-board processing capabilities.Multi-user detection (MUD) is a classic method of suppressing multiple access interference (MAI) in wireless communication, such as MMSE, Gaussian processregression (GPR) and other algorithms.Due to the inverse matrix required in the detection process, the algorithm complexity is usually cubic, and it is diff cult to directly apply to satellite platforms because of its limited processing capabilities.The conditional neural process combined the characteristics of the low complexity of the neural network and the data-eff cient of the Gaussian process.The neural network was used to parameterized the Gaussian process to avoided the inversion of the matrix, thereby reduced the computational complexity.The application of conditional neural process in MUD was studied.The simulation results showed that, while reduced complexity, conditional neural process also greatly improved the performance of bit error rate (BER).…”
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Sparse Adaptive Optimization Based on Low Rank Decomposition for Image Defect Detection by Daihong Jiang, Zhixiang Chen, Sanyou Zhang, Yunfei Li, Lu Zhao

Subjects: “…Low rank decomposition…”
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Analysis of algorithms for detecting traffic incidents on highways using stationary vehicle detectors by D. V. Navoi, D. V. Kapski, N. A. Filippova, I. N. Pugachev

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Development and Comparison of Interrupt-Based and Analog-to-Digital Converter Algorithms for Seed Counting in Precision Planters by A. Ghaffarnezhad, H. Navid, H. Karimi

Subjects: “…flow detection…”
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YOLO-EFM: Efficient traffic flow monitoring algorithm with enhanced multi-level information fusion by Shizhou Xu, Kaidi Cui

“…This paper presents an improved multi-scale object detection network, YOLO-EFM (Efficient Traffic Flow Monitoring Algorithm with Enhanced Multi-level Information Fusion). …”
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Identification of Low‐Value Defects in Infrared Images of Porcelain Insulators Based on STCE‐YOLO Algorithm by Shaotong Pei, Weiqi Wang, Chenlong Hu, Keyu Li, Haichao Sun, Mianxiao Wu, Bo Lan

“…To solve the above problems, this paper optimizes the small target and complex environment problems in the low‐value defect recognition of insulator infrared images, and proposes the STCE‐YOLO algorithm: based on YOLOv8, the deformable large kernel attention is used to improve the detection ability of small targets; then the cross‐modal contextual feature module is applied to Integrate the features of different scales to reduce the computation of the model. …”
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Outlier Traffic Flow Detection and Pattern Analysis Under Unplanned Disruptions: A Low-Rank Robust Decomposition Model by Zhipeng Duan

“…Outlier traffic flow detection under unplanned disruptions is vital for operational safety and management. …”
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The "Low Slow and Small" UAV target detection and tracking algorithm based on improved YOLOv7 and DeepSort by JIAN Yuhong, YANG Huiyue, WANG Xinggang, RONG Yisheng, ZHU Yukun

“…To improve the accuracy of Low altitude unmanned aerial vehicle(UAV) target detection and tracking, an improved UAV detection algorithm based on YOLOv7 and DeepSort framework is proposed. …”
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App-DDoS detection method using partial binary tree based SVM algorithm by Bin ZHANG, Zihao LIU, Shuqin DONG, Lixun LI

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LLD-YOLO: A Low-Light Object Detection Algorithm Based on Dynamic Weighted Fusion of Shallow and Deep Features by Wenhao Cai, Yajun Chen, Xiaoyang Qiu, Meiqi Niu, Jianying Li

“…Object detection in low-light scenarios has a wide range of applications, but existing algorithms often struggle to preserve the scarce low-level features in dark environments and exhibit limitations in localization accuracy for blurred edges and occluded objects, leading to suboptimal performance. …”
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Design and Implementation of Low-Complexity Multiple Symbol Detection Algorithm Using Hybrid Stochastic Computing in Aircraft Wireless Communications by Yukai Liu, Rongke Liu, Kairui Tian, Zheng Lu, Ling Zhao

“…The Multiple Symbol Detection (MSD) algorithm can effectively lower the demodulation threshold in Frequency Modulation (FM) technology, which is widely used in aircraft wireless communications due to its insensitivity to large Doppler shifts. …”
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Detection of low-altitude infrared small targets for UAVs using a density-based artificial bee colony algorithm by Haixia Wang, Hailong Wang, Fen Han

“…Abstract The objective of this paper is to address the issue of the inadequate detection accuracy of UAVs operating at low-altitudes in conditions of weak thermal signals. …”
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A Low Complexity Near-Optimal Detector Based on Teaching-Learning Algorithm for Massive MIMO by Hamid Amiriara, Mohammadreza Zahabi

“…In this paper, a low-complexity receiver is proposed using a Teaching-Learning based optimization (TLBO) heuristic algorithm for a large-scale system. …”
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