DV-DETR: Improved UAV Aerial Small Target Detection Algorithm Based on RT-DETR by Xiaolong Wei, Ling Yin, Liangliang Zhang, Fei Wu

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MA-YOLO: A Pest Target Detection Algorithm with Multi-Scale Fusion and Attention Mechanism by Yongzong Lu, Pengfei Liu, Chong Tan

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A Novel Denoising Algorithm of Electromagnetic Ultrasonic Detection Signal Based on Improved EEMD Method by Wenkang Gong, Qi Liu, Wenhao Du, Weichen Xu, Gang Wang

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YOLO-Helmet: A Novel Algorithm for Detecting Dense Small Safety Helmets in Construction Scenes by Guoliang Yang, Xinfang Hong, Yangyang Sheng, Liuyan Sun

“…However, the current algorithms for detecting helmet-wearing face several challenges, including high missed detection rates and low accuracy in detecting dense small safety helmets. …”
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Re-Parameterization After Pruning: Lightweight Algorithm Based on UAV Remote Sensing Target Detection by Yang Yang, Pinde Song, Yongchao Wang, Lijia Cao

“…Lightweight object detection algorithms play a paramount role in unmanned aerial vehicles (UAVs) remote sensing. …”
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Research on UAV Conflict Detection and Resolution Based on Tensor Operation and Improved Differential Evolution Algorithm by Zhichong Zhou, Guhao Zhao, Yiru Jiang, Yarong Wu, Jiale Yang, Lingzhong Meng

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Research on anomaly detection algorithm based on sparse variational autoencoder using spike and slab prior by Huahua CHEN, Zhe CHEN

“…Anomaly detection remains to be an essential and extensive research branch in data mining due to its widespread use in a wide range of applications.It helps researchers to obtain vital information and make better decisions about data by detecting abnormal data.Considering that sparse coding can get more powerful features and improve the performance of other tasks, an anomaly detection model based on sparse variational autoencoder was proposed.Firstly, the discrete mixed modelspike and slab distribution was used as the prior of variational autoencoder, simulated the sparsity of the space where the hidden variables were located, and obtained the sparse representation of data characteristics.Secondly, combined with the deep support vector network, the feature space was compressed, and the optimal hypersphere was found to discriminate normal data and abnormal data.And then, the abnormal fraction of the data was measured by the Euclidean distance from the data feature to the center of the hypersphere, and then the abnormal detection was carried out.Finally, the algorithm was evaluated on the benchmark datasets MNIST and Fashion-MNIST, and the experimental results show that the proposed algorithm achieves better effects than the state-of-the-art methods.…”
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Att-BEVFusion: An Object Detection Algorithm for Camera and LiDAR Fusion Under BEV Features by Peicheng Shi, Mengru Zhou, Xinlong Dong, Aixi Yang

“…This paper evaluates the effectiveness of the Att-BEVFusion fusion algorithm on the nuScenes dataset, and the results demonstrate that the algorithm achieved 72.0% mean average precision (mAP) and 74.3% nuScenes detection score (NDS), with an advanced detection accuracy of 88.9% and 91.8% for single-item detection of automotive and pedestrian categories, respectively.…”
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An analytical pressure-velocity fusion algorithm-empowered flexible sensing patch for flight parameter detection by Yunfan Li, Zihao Dong, Zheng Gong, Zhiqiang Ma, Xin Ke, Tianyu Sheng, Xiaochang Yang, Xilun Ding, Yonggang Jiang

“…To solve flight parameters with the flexible sensing patch, we develop an analytical pressure-velocity fusion algorithm, enabling fast response and high accuracy in flight parameter detection. …”
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Magnetic Source Detection Using an Array of Planar Hall Effect Sensors and Machine Learning Algorithms by Miki Vizel, Roger Alimi, Daniel Lahav, Moty Schultz, Asaf Grosz, Lior Klein

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LG-YOLOv8: A Lightweight Safety Helmet Detection Algorithm Combined with Feature Enhancement by Zhipeng Fan, Yayun Wu, Wei Liu, Ming Chen, Zeguo Qiu

“…Addressing the issues of high parameter values and sluggish detection speed in current safety helmet detection algorithms, a feature-enhanced lightweight algorithm, LG-YOLOv8, was introduced. …”
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Evaluating and Enhancing Face Anti-Spoofing Algorithms for Light Makeup: A General Detection Approach by Zhimao Lai, Yang Guo, Yongjian Hu, Wenkang Su, Renhai Feng

“…The experimental outcomes confirm that the proposed algorithm exhibits superior detection capabilities when handling light makeup faces.…”
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Developing an Algorithm for Detecting Suspicious Trades in Tehran Stock Exchange Based on Spoof Trading Model by Reza Tehrani, Saeed Fallahpour, Hamid Nouralidokht

“…More specifically, this paper studies manipulated stocks by looking at market microstructure (intraday transactions) and aims to introduce an algorithm for detecting suspicious trades so that regulators can detect them beforehand. …”
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Securing IoT Communications via Anomaly Traffic Detection: Synergy of Genetic Algorithm and Ensemble Method by Behnam Seyedi, Octavian Postolache

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Early Detection of Congenital Heart Diseases among Infants Using Artificial Neural Network Algorithm by Lucy Ifeyinwa Ezigbo, Anthony Kwubeghari, Francis Okoye

“…After the data processing stage, Artificial Neural Network (ANN) algorithm is adopted and trained with the data to generate the model for the detection of the CHD. …”
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MSFA-YOLO: A Multi-Scale SAR Ship Detection Algorithm Based on Fused Attention by Zhao Liangjun, Ning Feng, Xi Yubin, Liang Gang, He Zhongliang, Zhang Yuanyang

“…Exhibiting superior performance to existing SAR ship detection models in terms of accuracy, the MSFA-YOLO algorithm represents a significant advancement, establishing itself as the current state-of-the-art algorithm in SAR ship detection.…”
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Research and Application of a Multitarget Detection Algorithm Based on Improved YOLOv8 for Indoor Objects by Yanzhen Wang, Wei Wang, Xiaolong Zhou, Xubin Dong, Jianyong Li, Qi Zhao, Xinyu Yang, Yao Wang

“…The goal is to achieve efficient multitarget detection of everyday objects and to improve the accuracy and recall of the detection algorithm. …”
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Adaptive convolutional neural network-based principal component analysis algorithm for the detection of manufacturing data by Tsun-Kuo Lin

“…Herein, an adaptive convolutional neural network (CNN)-based principal component analysis (PCA) algorithm for the detection of manufacturing data is proposed. …”
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Rice-SVBDete: a detection algorithm for small vascular bundles in rice stem’s cross-sections by Xiaoying Zhu, Weiyu Zhou, Jianguo Li, Jianguo Li, Mingchong Yang, Mingchong Yang, Haiyu Zhou, Haiyu Zhou, Jiada Huang, Jiada Huang, Jiahua Shi, Jun Shen, Guangyao Pang, Lingqiang Wang, Lingqiang Wang, Lingqiang Wang

“…Accurate measurement of their structure and distribution is essential for improving rice breeding and cultivation strategies. However, the detection of small vascular bundles from cross-sectional images is challenging due to their tiny size and the noisy background typically present in microscopy images.MethodsTo address these challenges, we propose Rice-SVBDete, a specialized deep learning-based detection algorithm for small vascular bundles in rice stem cross-sections. …”
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Improved Algorithm for Vehicle Bottom Safety Detection Based on YOLOv8n: PSP-YOLO by Di Zhao, Yulin Cheng, Sizhe Mao

“…To address these issues and improve the real-time performance of under-vehicle safety inspection, the YOLOv8n object-detection algorithm was enhanced, resulting in the PSP-YOLO algorithm. …”
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