Highway subgrade stability prediction model based on depth separation convolutional fusion network by Yubian Wang

“…To promote the ability of high-precision highway maintenance and detection and solve the situation of false detection or missing detection of road defects, it is necessary to establish a monitoring mechanism of multi-scale feature fusion. …”
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Image-Based Malicious Network Traffic Detection Framework: Data-Centric Approach by Doo-Seop Choi, Taeguen Kim, Boojoong Kang, Eul Gyu Im

“…This paper focused on feature engineering instead of AI algorithm selections, presenting an approach that uniquely balances detection accuracy with computational efficiency through strategic dimensionality reduction. …”
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RST-YOLOv8: An Improved Chip Surface Defect Detection Model Based on YOLOv8 by Wenjie Tang, Yangjun Deng, Xu Luo

“…We propose an enhanced chip surface defect detection algorithm based on an improved version of YOLOv8, termed RST-YOLOv8. …”
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Zipper Pattern: An Investigation into Psychotic Criminal Detection Using EEG Signals by Gulay Tasci, Prabal Datta Barua, Dahiru Tanko, Tugce Keles, Suat Tas, Ilknur Sercek, Suheda Kaya, Kubra Yildirim, Yunus Talu, Burak Tasci, Filiz Ozsoy, Nida Gonen, Irem Tasci, Sengul Dogan, Turker Tuncer

“…In the feature selection phase of the proposed XFE model, an iterative neighborhood component analysis (INCA) feature selector was used to choose the most distinctive features. …”
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An Accurate Book Spine Detection Network Based on Improved Oriented R-CNN by Haibo Ma, Chaobo Wang, Ang Li, Aide Xu, Dong Han

“…However, the varying tilt angles and diverse aspect ratios of books on library shelves often reduce the effectiveness of conventional object detection algorithms. To address these challenges, this study proposes an enhanced oriented R-CNN algorithm for book spine detection. …”
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A Method of Fatigue Driving State Detection Based on Deep Learning by XIONG Qunfang, LIN Jun, YUE Wei

“…Current domestic and overseas fatigue recognition algorithms are implemented using fatigue features which are mostly singular and man-made. …”
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Lightweight malicious domain name detection model based on separable convolution by Luhui YANG, Huiwen BAI, Guangjie LIU, Yuewei DAI

“…The application of artificial intelligence in the detection of malicious domain names needs to consider both accuracy and calculation speed,which can make it closer to the actual application.Based on the above considerations,a lightweight malicious domain name detection model based on separable convolution was proposed.The model uses a separable convolution structure.It first applies depthwise convolution on every input channel,and then performs pointwise convolution on all output channels.This can effectively reduce the parameters of convolution process without impacting the effectiveness of convolution feature extraction,and realize faster convolution process while keeping high accuracy.To improve the detection accuracy considering the imbalance of the number and difficulty of positive and negative samples,a focal loss function was introduced in the training process of the model.The proposed algorithm was compared with three typical deep-learning-based detection models on a public data set.Experimental results denote that the proposed algorithm achieves detection accuracy close to the state-of-the-art model,and can significantly improve model inference speed on CPU.…”
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Optimization of particle filter tracking algorithm based on weakly supervised attribute learning by Hui Zhang, Dawang Shen

“…This method combines weakly supervised learning with energy function optimization to raise the efficiency of image feature annotation in object detection models. Besides, to raise the robustness and accuracy of target tracking algorithms in complex environments, an improved particle filter tracking method based on accelerated robust feature matching is proposed. …”
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Robust Resilience Blocks Detection Problem in Dynamic Social Networks by Yuxin Gao, Jianming Zhu, Peikun Ni, Guoqing Wang

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Design and Optimization of Hybrid CNN-DT Model-Based Network Intrusion Detection Algorithm Using Deep Reinforcement Learning by Lu Qiu, Zhiping Xu, Lixiong Lin, Jiachun Zheng, Jiahui Su

“…To address these challenges, this study proposes an innovative network intrusion detection algorithm that combines convolutional neural networks (CNNs) and decision trees (DTs) together, named CNN-DT algorithm. …”
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Kans-Unet Model and Its Application in Image Patch-Shaped Detection by Xingsu Li, Zhong Li, Jianping Huang, Ying Han, Kexin Zhu, Bo Hao, Junjie Song, Yumeng Huo

“…The experimental results show that the KANs-Unet algorithm exhibits better detection performance compared to current mainstream semantic segmentation algorithms in the task of detecting abnormal speckle areas. …”
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Research on Arthroscopic Images Bleeding Detection Algorithm Based on ViT-ResNet50 Integrated Model and Transfer Learning by Zewen Liu, Shaoyi Zhou, Jianqiao Chu, Zhiyuan Chai, Dongdong Chang, Yi Yuan, Jinling Qin, Xiancheng Wang

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Optimized Error Detection and Correction in ATM Networks Using the Enhanced Berlekamp Massey Algorithm With Hybrid Automatic Repeat Request by Mahmut Aykac

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Design of a novel noise resilient algorithm for fault detection in wind turbines on supervisory control and data acquisition system by Muhammad Irfan, Nabeel Ahmed Khan, Muhammad Abubakar, Zohaib Mushtaq, Tomasz Jakubowski, Paweł Sokołowski, Grzegorz Nawalany, Saifur Rahman

“…The P-RF algorithm achieved 99.72% accuracy in diagnosing the status of the SCADA-based wind turbine although with a slightly higher computational complexity than a baseline Random Forest algorithm. …”
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UCA-YOLOv8n: a real-time and efficient fruit chunks detection algorithm for meal-assistance robot by Fei Liu, Mingyue Hu

“…Methods We propose an improved YOLOv8n algorithm optimized for real-time, high-accuracy fruit chunk detection. …”
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Guided wave signal‐based sensing and classification for small geological structure by Hongyu Sun, Jiao Song, Shanshan Zhou, Qiang Liu, Xiang Lu, Mingming Qi

“…Then, the TUCKER‐based NTSF algorithm was employed for feature extraction and classification. …”
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Ground Segmentation Algorithm for Sloped Terrain and Sparse LiDAR Point Cloud by Victor Jimenez, Jorge Godoy, Antonio Artunedo, Jorge Villagra

“…Distinguishing obstacles from ground is an essential step for common perception tasks such as object detection-and-tracking or occupancy grid maps. Typical approaches rely on plane fitting or local geometric features, but their performance is reduced in situations with sloped terrain or sparse data. …”
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A Context-Aware Doorway Alignment and Depth Estimation Algorithm for Assistive Wheelchairs by Shanelle Tennekoon, Nushara Wedasingha, Anuradhi Welhenge, Nimsiri Abhayasinghe, Iain Murray

“…These challenges highlight a pressing need for intelligent doorway detection algorithm for assistive wheelchairs that go beyond traditional object detection. …”
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A Fast and Cost-Effective Electronic Nose Model for Methanol Detection Using Ensemble Learning by Bilge Han Tozlu

“…A Voting Classifier, an ensemble model, was used with Linear Discriminant Analysis, Support Vector Machines, and Extra Trees algorithms. The Voting Classifier achieved 85.88% classification accuracy before and 81.85% after feature selection. …”
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Rapid detection of wheel tread defects for YOLO-v5 trains based on residual attention by ZHANG Changfan, XU Yifu, HE Jing, YANG Haonan

“…In respect of large noise interference of wheel tread and insufficient feature fusion of traditional detection algorithms, in order to achieve fast and accurate detection of wheel tread defects, a method for rapid detection of wheel tread defects for YOLO-v5 trains based on residual attention was proposed. …”
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