Adaptive random early detection algorithm based on network traffic level grade prediction by Debin WEI, Chengsheng PAN, Li YANG, Zuoren YAN

“…In view of the problem that the calculation of average queue length and maximum packet drop probability in random early detection algorithm and its variants reflect the changes of network traffic slowly, an adaptive random early detection algorithm based on network traffic level grade prediction was proposed.Based on the statistical characteristics of self-similar network traffic, the transition probability table of network traffic level grade was established, and a grade prediction method of self-similar network traffic level with low complexity and high accuracy was proposed.Furthermore, the prediction results were applied to calculate the average queue length in equal interval and adjust the maximum packet drop probability.Under the condition of fixed and variable bottleneck link capacity, it is found that regardless of the degree of self-similarity of network traffic, the proposed algorithm can improve the throughput and packet loss rate, especially when the Hurst parameter is large and the traffic is light.…”
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Small target detection algorithm based on the fusion attention mechanism and multi-layer convolution. by Xiujing Li, Haifei Zhang, Yiliu Hang, Hao Chen

“…In the realm of unmanned aerial vehicles, we proposed an enhanced small target detection algorithm, MGAC-YOLO, to address the challenges of missed detections and low accuracy associated with small target identification. …”
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Design and Validation of a Lightweight Entropy-Based Intrusion Detection Algorithm for Automotive CANs by Jiacheng Chen, Zhifu Wang

“…To address this, we propose a lightweight intrusion detection algorithm leveraging information entropy to analyze side-channel CAN message ID distributions. …”
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Research on Target Detection Algorithm for Solder Joint Defects Based on the Improved YOLOv8 by Chengkai Zhang, Xiaocui Feng, Pujun Mao, Fuyan Lv

“…Aiming at the problem of low accuracy in solder joint defect detection caused by the complex background and difficult to extract defect features of circuit boards using through-hole technology (THT), an improved YOLOv8 solder joint defect target detection algorithm was proposed. …”
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A lightweight algorithm for steel surface defect detection using improved YOLOv8 by Shuangbao Ma, Xin Zhao, Li Wan, Yapeng Zhang, Hongliang Gao

“…Abstract In response to the issues of low precision, a large number of parameters and high model complexity in steel surface defect detection, a lightweight algorithm using improved YOLOv8 is proposed. …”
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A small‐target traffic sign detection algorithm based on partial conv and atrous spatial pyramid by Yuqi Li, Zijian Wang, Han Zhang, Xinpeng Yao, Zhou Zhou, Xin Cheng

“…The deep learning‐based algorithm proposed in this paper aims to address the issue of low detection accuracy caused by the small size and high density of traffic signs in real‐world traffic scenarios. …”
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Fault Detection in Blowfish Algorithm Using FPGA-Based Modified Decision Tree Approach by Joseph Anthony Prathap, Mithileysh Sathiyanarayanan

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Target Detection Algorithm Based on Global Feature Fusion in Parallel Dual Path Backbone by QIU Yunfei, XIN Hao

“…Experimental results show that the proposed algorithm improves the detection performance in complex scenes, and has low requirements for computing power and other resources.…”
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Flexible Adaptive Marine Predator Algorithm and Its Application in Fault Detection for Wind Turbines by WANG Wen, YI Jiabiao

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DScanNet: Packaging Defect Detection Algorithm Based on Selective State Space Models by Yirong Luo, Yanping Du, Zhaohua Wang, Jingtian Mo, Wenxuan Yu, Shuihai Dou

“…Through experiments on its own dataset, BIGC-LP, DScanNet achieves a high accuracy of 96.8% on the defect detection task compared with the current mainstream detection algorithms, while the number of model parameters and the computational volume are effectively controlled.…”
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A comparative assessment of machine learning models and algorithms for osteosarcoma cancer detection and classification by Amoakoh Gyasi-Agyei

“…The empirical model based on the extra trees algorithm and fitted to class-balanced dataset via random oversampling and multicollinearity removed via principal component analysis proved to be the best, as it detected and classified osteosarcoma cancer in 10 ms with 97.8% area under the receiver operating characteristics curve and acceptably low false alarm and misdetection. …”
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Surface Defect Detection Algorithm for Wind Turbine Blades Based on HSCA-YOLOv7 by Bing LI, Yunshan BAI, Kuan ZHAO, Congbin GUO, Yongjie ZHAI

“…The blade is one of the key components of the wind turbine, which is vulnerable to the impact of natural environmental factors, resulting in gel coat falling off, cracks, corrosion, and other damage and thus affecting the efficiency of wind power generation and the safety of wind turbine operation. A defect detection algorithm for wind turbine blades based on HSCA-YOLOv7 is proposed to address the issues of inconsistent defect scale, inaccurate positioning, and low detection accuracy in wind turbine blade images by aerial photography. …”
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Multi-strategy enhanced marine predator algorithm: performance investigation and application in intrusion detection by Zhongmin Wang, Yujun Zhang, Jun Yu, YuanYuan Gao, Guangwei Zhao, Essam H. Houssein, Rui Zhong

“…Therefore, this paper presents a Multi-strategy Enhanced Marine predator algorithm (MEMPA), where (1) a low-discrepancy Sobol sequence is introduced to generate promising initial solutions in the high-dimensional search domain, (2) the mutualism mechanism is integrated to enhance the ability to escape from local optima, and (3) a distance-based selection scheme is embedded to enhance the diversity of the population during optimization. …”
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Fast Identification and Detection Algorithm for Maneuverable Unmanned Aircraft Based on Multimodal Data Fusion by Tian Luan, Shixiong Zhou, Yicheng Zhang, Weijun Pan

“…For practical deployment, we further enhance tracking robustness through an improved BoT-SORT algorithm within an interactive multiple model framework, achieving 91.3% MOTA and 93.0% IDF1 under low-light conditions. …”
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Detection Algorithm for Air Duct Clamp on Trains Based on RSA-YOLOv10n by WANG Dairong, ZHAO Yuhong, QU Xiaozhang, LIU Yi

“…To address challenges in the detection of air duct clamps due to factors such as dim environments and small objects in train detection, such as insufficient detection accuracy and low detection efficiency, this paper proposes a RSA-YOLOv10n-based detection algorithm, developed utilizing a dataset of air duct clamps collected from trains. …”
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YOLO-SAG: An improved wildlife object detection algorithm based on YOLOv8n by Lingli Chen, Gang Li, Shunkai Zhang, Wenjie Mao, Mei Zhang

“…This paper proposes a wildlife target detection algorithm based on improved YOLOv8n - YOLO-SAG, which aims to balance accuracy and speed. …”
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The Accuracy of Algorithms Used by Artificial Intelligence in Cephalometric Points Detection: A Systematic Review by Júlia Ribas-Sabartés, Meritxell Sánchez-Molins, Nuno Gustavo d’Oliveira

“…Six were high-risk, and seven were low-risk. Convolutional neural networks (CNN)-based AI algorithms showed point localization accuracy ranging from 64.3 to 97.3%, with a mean error of 1.04 mm ± 0.89 to 3.40 mm ± 1.57, within the clinical range of 2 mm. …”
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Fault detection algorithm for underground conveyor belt deviation based on improved RT-DETR by AN Longhui, WANG Manli, ZHANG Changsen

“…The method requires setting specific thresholds and is easily affected by environmental factors, resulting in slow detection speed and low accuracy. To address the issue, an underground conveyor belt deviation fault detection algorithm based on an improved real-time detection transformer (RT-DETR) was proposed. …”
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Detection algorithm for wearing safety helmet under mine based on improved YOLOv5s by Yuanbin WANG, Sixiong WEI, Huaying WU, Yu DUAN, Meng LIU

“…Aiming at the problems of low accuracy and high missed detection rate of personnel safety helmet detection algorithm caused by complex environment under mine, an improved mine safety helmet detection algorithm based on YOLOv5s is proposed. …”
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Voice pathology detection using machine learning algorithms based on different voice databases by Nurul Mu'azzah Abdul Latiff, Fahad Taha Al-Dhief, Nurul Fariesya Suhaila Md Sazihan, Marina Mat Baki, Nik Noordini Nik Abd. Malik, Musatafa Abbas Abbood Albadr, Ali Hashim Abbas

“…The application of machine learning in analyzing voice disorders has become crucial for non-invasive voice pathology detection using voice signals. However, current systems face challenges such as low detection accuracy, limited databases, and evaluation metrics. …”
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