A New YOLOv4-tiny Neural Network and Its Application on Object Detection of Power-line Isolators by SONG Li-bo, FEI Yan-qiong

“…In term of 58% weight files, 66.7% computation, higher 10% detection quantity and lower 10% false detection quantity, it is proved that the new YOLOv4-tiny algorithm is efficient and practical in comparison to the standard YOLOv4-tiny algorithm.…”
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A Transport Mode Detection Framework Based on Mobile Phone Signaling Data Combined with Bus GPS Data by Shuqi Zhong, Jiatao Chen, Ming Cai

“…Finally, we built a ground truth dataset and compared the recognition accuracies under different features and classification models. The result shows that the transport mode detection accuracies of the proposed framework with the GBDT, XGBoost, and LightGBM algorithms are all higher than 94%.…”
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An Improved YOLOv8-Based Dense Pedestrian Detection Method with Multi-Scale Fusion and Linear Spatial Attention by Han Gong, Tian Li, Lijuan Wang, Shucheng Huang, Mingxing Li

“…To address the issue of missed detection for small-scale occluded pedestrians in dense scenes, this paper proposes an improved YOLOv8 detection algorithm named Dense-YOLOv8. …”
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Fault Detection and Isolation Strategy for Brake Actuation Units of High-Speed Trains Under Variable Operating Conditions by Jingxian Ding, Tianyu Xia, Xinzhou Wu, Shize Zheng, Tianyi Wang

“…Thirdly, fault detection and isolation were realized based on PCA and the IRBCP algorithm. …”
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Prediction of Total Soluble Solids in Apricot Using Adaptive Boosting Ensemble Model Combined with NIR and High-Frequency UVE-Selected Variables by Feng Gao, Yage Xing, Jialong Li, Lin Guo, Yiye Sun, Wen Shi, Leiming Yuan

“…This study develops an advanced framework integrating adaptive boosting (Adaboost) ensemble learning with high-frequency spectral variables selected by uninformative variable elimination (UVE) for the rapid non-destructive detection of fruit quality. Near-infrared (NIR) spectra (1000~2500 nm) were acquired and then preprocessed through robust principal component analysis (ROBPCA) for outlier detection combined with z-score normalization for spectral pretreatment. …”
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An Improved Machine Learning-Based Model for Detecting and Classifying PQDs with High Noise Immunity in Renewable-Integrated Microgrids by Irfan Ali Channa, Dazi Li, Mohsin Ali Koondhar, Fida Hussain Dahri, Ibrahim Mahariq

“…In the optimized-kernel SVM model, computing power is enhanced for classifying multiple PQ events based on the local density and leave-one-out (LOO) algorithm. To get higher separation in feature space, the kernel width of each sample is estimated based on the local density. …”
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Accurate Detection and Tracking of Small-Scale Vehicles in High-Altitude Unmanned Aerial Vehicle Bird-View Imagery by Heshan Zhang, Xin Tan, Mengwei Fan, Cunshu Pan, Zhanji Zheng, Shuang Luo, Jin Xu

“…Especially in tasks with long distances, extensive backgrounds, and small objects, it increases the difficulty of localization and regression, which can easily lead to missed detections and false positives. This paper proposes a detection-based small-scale vehicle tracking framework that integrates an improved YOLOX network and the DeepSORT algorithm to address these issues. …”
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An Unsupervised Remote Sensing Image Change Detection Method Based on RVMamba and Posterior Probability Space Change Vector by Jiaxin Song, Shuwen Yang, Yikun Li, Xiaojun Li

“…In the RFCC, we propose an unsupervised remote sensing image segmentation algorithm based on the Mamba model, i.e., RVMamba differentiable feature clustering, which introduces two loss functions as constraints to ensure that RVMamba achieves accurate segmentation results and to supply the CSBN module with high-quality training samples. …”
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PCB Electronic Component Soldering Defect Detection Using YOLO11 Improved by Retention Block and Neck Structure by Youzhi Xu, Hao Wu, Yulong Liu, Xing Zhang

“…The single-stage target detection algorithm has a faster running time, but the detection accuracy needs to be improved. …”
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Advanced Point Cloud Techniques for Improved 3D Object Detection: A Study on DBSCAN, Attention, and Downsampling by Wenqiang Zhang, Xiang Dong, Jingjing Cheng, Shuo Wang

“…Firstly, we integrated a point cloud processing module utilizing the DBSCAN clustering algorithm to effectively segment and extract critical features from the point cloud data. …”
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Deep convolutional neural network (DCNN)-based model for pneumonia detection using chest x-ray images by S. I. Ele, U. R. Alo, H. F. Nweke, A. H. Okemiri, E. O. Uche-Nwachi

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Cascaded Detection Method for Ship Targets Using High-Frequency Surface Wave Radar in the Time–Frequency Domain by Zhiqing Yang, Hao Zhou, Yingwei Tian, Gan Liu, Bing Zhang, Yao Qin, Peng Li, Weimin Huang

“…Due to noise interference, ship echoes in the noise region often fall below the detection threshold, leading to missed detections. …”
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A Preprocessing Method for Insulation Pull Rod Defect Dataset Based on the YOLOv5s Object Detection Network by Xuetong Li, Meng Cong, Bo Liu, Xianhao Fan, Weiqi Qin, Fangwei Liang, Chuanyang Li, Jinliang He

“…Thus, this work proposes a data preprocessing method for the insulation pull rod defect feature dataset. In this work, the YOLOv5s algorithm is used to detect defects in insulation pull rod images, creating a dataset with five defect categories. …”
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Real-Time Series Arc Fault Detection and Appliances Classification in AC Networks Based on Competing Convolutional Kernels by Francesco Ferracuti, Riccardo Felicetti, Luca Cavanini, Patrick Schweitzer, Andrea Monteriu

“…To reduce inference time and optimize the algorithm for embedded control units, a feature reduction strategy is employed. …”
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Detection and Strong Classification of Natural Weld Defects by Magneto-Optical Imaging Under Rotating Magnetic Field Excitation by Yanfeng Li, Xiangdong Gao, Yanxi Zhang

“…A magneto-optical (MO) imaging detection system excited by a rotating magnetic field is proposed for feature extraction and detection classification of invisible natural weld defects. …”
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Effective DDoS attack detection in software-defined vehicular networks using statistical flow analysis and machine learning. by Himanshi Babbar, Shalli Rani, Maha Driss

“…The proposed methodology aims to: (i) analyze statistical flow and compute entropy, and (ii) implement Machine Learning (ML) algorithms within SDN Intrusion Detection Systems for Internet of Things (IoT) environments. …”
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Unsupervised detection of high-frequency oscillations in intracranial electroencephalogram: promoting a valuable automated diagnostic tool for epilepsy by Wenjing Chen, Tongzhou Kang, Md Belal Bin Heyat, Jamal E. Fatima, Yuanning Xu, Dakun Lai

“…The CVAE model is trained for dimensionality reduction and feature reconstruction, followed by clustering of the reconstructed maps using the K-means algorithm for automated HFOs detection.ResultsEvaluation of the proposed unsupervised method on clinical iEEG data demonstrates its superior performance compared to traditional supervised models. …”
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Detection of Malicious Office Open Documents (OOXML) Using Large Language Models: A Static Analysis Approach by Jonas Heß , Kalman Graffi

“…As a supplementary tool to contemporary antivirus software, it is currently able to assist in the analysis of malicious Microsoft Office documents by identifying and summarising potentially malicious indicators with a foundation in evidence, which may prove to be more effective with advancing technology and soon to surpass tailored machine learning algorithms, even without the utilisation of signatures and detection rules. …”
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Accurate and affordable multi-cancer early detection and localization via plasma cfDNA multi-omic profiling by Pin Cui, Weihuang He, Mingji Feng, Hanming Lai

“…Background: Early detection of major cancers, including HCC, lung cancer, colotectal cancer and etc., can improve prognosis, but has not yet been clinically implemented due to lack of accurate and affordable means. …”
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Research on a Wear Defect Detection Method for a Switch Sliding Baseplate Based on Improved Yolov5 by Qing Jiang, Ruipeng Gao, Yan Zhao, Wenzhen Yu, Zhuofan Dang, Shiyi Deng

“…To address the above-mentioned issues, the YOLOv5s algorithm has been refined and subsequently applied to the detection of micro-cutting defects generated by wear on the switch sliding baseplate. …”
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