An insulator target detection algorithm based on improved YOLOv5 by Bing Zeng, Zhihao Zhou, Yu Zhou, Dilin He, Zhanpeng Liao, Zihan Jin, Yulu Zhou, Kexin Yi, Yunmin Xie, Wenhua Zhang

“…Abstract Drone inspections are widely utilized in the detection of insulators in power lines. To address issues with traditional object detection algorithms, such as large parameter counts, low detection accuracy, and high miss rates, this paper proposes an insulator detection algorithm based on an improved YOLOv5 model. …”
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MGL-YOLO: A Lightweight Barcode Target Detection Algorithm by Yuanhao Qu, Fengshou Zhang

“…To address this issue, this paper proposes MGL-YOLO, a lightweight one-dimensional barcode detection network based on an improved YOLOv8, which aims to achieve a high detection accuracy at low computational cost. …”
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Ship Plate Detection Algorithm Based on Improved RT-DETR by Lei Zhang, Liuyi Huang

“…To address the challenges in ship plate detection under complex maritime scenarios—such as small target size, extreme aspect ratios, dense arrangements, and multi-angle rotations—this paper proposes a multi-module collaborative detection algorithm, RT-DETR-HPA, based on an enhanced RT-DETR framework. …”
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YOLOX-S-TKECB: A Holstein Cow Identification Detection Algorithm by Hongtao Zhang, Li Zheng, Lian Tan, Jiahui Gao, Yiming Luo

“…Currently, cow identification faces challenges such as poor recognition accuracy, large data volumes, weak model generalization ability, and low recognition speed. Therefore, this paper proposes a cow identification method based on YOLOX-S-TKECB. (1) Based on the characteristics of Holstein cows and their breeding practices, we constructed a real-time acquisition and preprocessing platform for two-dimensional Holstein cow images and built a cow identification model based on YOLOX-S-TKECB. (2) Transfer learning was introduced to improve the convergence speed and generalization ability of the cow identification model. (3) The CBAM attention mechanism module was added to enhance the model’s ability to extract features from cow torso patterns. (4) The alignment between the apriori frame and the target size was improved by optimizing the clustering algorithm and the multi-scale feature fusion method, thereby enhancing the performance of object detection at different scales. …”
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Weed detection on embedded systems using computer vision algorithms by D. Shadrin, S. Illarionova, R. Kasatov, M. Akimenkova, G. Rudensky, E. Erhan

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An algorithm for cardiac disease detection based on the magnetic resonance imaging by Heng Li, Qingni Yuan, Yi Wang, Pengju Qu, Chunhui Jiang, Hu Kuang

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Machine learning algorithm for the rapid and accurate detection of Plasmodium falciparum by Mr Andrew Hill

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Lightweight detection algorithms for small targets on unmanned mining trucks by Shuoqi CHENG, Yilihamu·YAERMAIMAITI, Lirong XIE, Xiyu LI, Ying MA

“…Therefore, to address the issues of high parameter count, large model size, and low detection accuracy for small and occluded targets in open-pit mining scenarios, we propose the Lightweight Unmanned Mining Truck Detection Algorithm LWHP (Lightweight High-Precision). …”
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Accuracy and precision of fixation locations recorded with the low-cost Eye Tribe tracker in different experimental set-ups by Kristien Ooms, Lien Dupont, Lieselot Lapon, Stanislav Popelka

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Target Detection in Low Grazing Angle with Adaptive OFDM Radar by Yang Xia, Zhiyong Song, Zaiqi Lu, Hao Wu, Qiang Fu

“…Multipath effect is the main factor of deteriorating target detection performance in low grazing angle scenario, which results from reflections on the ground/sea surface. …”
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Fast OMP algorithm and its FPGA implementation for compressed sensing‐based sparse signal acquisition systems by Shirshendu Roy, Debiprasad P. Acharya, Ajit K. Sahoo

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Simulation of Patch Field Effect in Space-Borne Gravitational Wave Detection Missions by Mingchao She, Xiaodong Peng, Li-E Qiang

Subjects: “…space-borne gravitational wave detection…”
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A Deep Learning-Based Algorithm for Ceramic Product Defect Detection by Junxiang Diao, Hua Wei, Yawei Zhou, Zhihua Diao

“…In the field of ceramic product defect detection, traditional manual visual inspection methods suffer from low efficiency and high subjectivity, while existing deep learning algorithms are limited in detection efficiency due to their high complexity. …”
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Research on algorithm for improving imaging accuracy of CFRP low speed impact damage by WU Xiangnan, CHENG Xiaojin, LI Qixin, SHANG Jianhua

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Situation Awareness and Tracking Algorithm for Countering Low-Altitude Swarm Target Threats by Nannan Zhu, Fuli Zhong, Xueyue Lei, Guo Niu, Hongtu Xie, Yue Zhang

“…To address these challenges, we design a digital staring radar system integrated with an adaptive random matrix method for efficient tracking of low-altitude swarm targets. The system achieves full spatiotemporal coverage without beam scanning or complex resource scheduling, enabling simultaneous detection and tracking of multiple targets. …”
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A new classification algorithm for low concentration slurry based on machine vision by Chuanzhen Wang, Xinyi Wang, Andile Khumalo, Fengcheng Jiang, Jintao Lv

“…The findings indicated the excellent performance in low concentration detection of coal slurry throughout this study.…”
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Position related lightweight Sybil detection approach in VANET by Yan XIN, Xia FENG, Ting-ting LI

“…In VANET,the Sybil attack simultaneously using multiple forged identities can easily cause the injustice of resource usage and make networks in a mess by distributing false messages.To solve this problem,an event-driven lightweight algorithm was proposed,which could identify vehicles false position quickly.When one vehicle appeared inside another's safety zone,a geometrical cross-recognition algorithm to calculate the overlap between vehicles to detect false position claiming was presented.At the same time,according to the neighbors within the confirming vehicle's radio range,position deviation matrix was established further to identify the Sybil node of two overlap vehicles.The performance analysis and simulation results show that the lightweight algorithm driven by safety zone demonstrates fast identification and high detection rate,especially when GPS error is very low.The imported safety zone can also balance the communication load impacting by heavy vehicular density.And the communication processing delay is lower than other approaches.…”
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Panel defect detection algorithm based on improved Faster R-CNN by Chen Wanqin, Tang Qingshan, Huang Tao

“…In view of the low precision and low efficiency of panel surface defect detection, this paper proposes an optimized defect detection algorithm based on Faster R-CNN. …”
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M-APSK phase detection algorithm and parallel carrier synchronization method by Hao HUAN, Kexue REN

“…In order to realize the precise phase correction of high order modulation in M-APSK modem, the Q-power non-data aided phase detection method recommended by DVB-S2 standard for 16APSK and 32APSK was extended to 64APSK, 128APSK and 256APSK.An improved algorithm was proposed to solve the problem of unstable loop operation when the proportion of constellation points used for phase detection in high-order modulation was low.By using threshold judgment on the amplitude of the received symbol after power normalization, phase detection was performed only when the amplitude was higher than the threshold, and the filter state and phase compensation value were not changed when the amplitude was lower than the threshold, so as to improve the phase detection effectiveness and reliability of constellation points and reduce the lock threshold.Aiming at the problem that the symbol rate of high-speed data transmission was very high but the working clock frequency of the processor was relatively low, a parallel carrier synchronization method for M-APSK was proposed, which could meet the needs of the receiver’s working clock.Compared with the traditional constant coding and modulation (CCM) carrier synchronization loop, the parallel method could also be applied to the frequency tracking of variable coding and modulation (VCM) system.…”
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A lightweight detection algorithm of PCB surface defects based on YOLO. by Shiwei Yu, Feng Pan, Xiaoqiang Zhang, Linhua Zhou, Liang Zhang, Jikui Wang

“…Aiming at the problems of low accuracy and large computation in the task of PCB defect detection. …”
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