EGRN-YOLO: An Enhanced Multi-View Remote Sensing Detection Algorithm for Onshore Wind Turbines Based on YOLOv7 by Renzheng Xue, Haiqiang Xu, Qianlong Wu

“…Wind turbines, as the core components of wind power generation systems, play a crucial role in determining the overall generation efficiency and operational safety. However, the challenges posed by complex backgrounds, significant variations in the scale of wind turbine targets, and arbitrary orientations in unmanned aerial vehicle (UAV) remote sensing images have significantly increased the difficulty of real-time wind turbine detection. …”
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YOLO-SSFA: A Lightweight Real-Time Infrared Detection Method for Small Targets by Yuchi Wang, Minghua Cao, Qing Yang, Yue Zhang, Zexuan Wang

“…Infrared small target detection is crucial for military surveillance and autonomous driving. …”
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Traffic anomaly event detection and auxiliary decision-making based on large language models by LI Yanying, WANG Xinyu, WANG Xiao, SUN Changyin

“…The results show that compared with traditional methods, TMGPT significantly improves the accuracy of detection and reduced response time in the detection and assisted decision-making of abnormal traffic events, which demonstrates the application potential of large language models in complex urban traffic management.…”
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A lightweight UAV target detection algorithm based on improved YOLOv8s model by Fubao Ma, Ran Zhang, Bowen Zhu, Xirui Yang

“…Second, Parameter Shared Convolution Head (PSC-Head) is designed to enhance detection efficiency and further minimize model size. …”
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Sowing, Monitoring, Detecting: A Possible Solution to Improve the Visibility of Cropmarks in Cultivated Fields by Filippo Materazzi

“…This study explores the integration of UAS-based multispectral remote sensing and targeted agricultural practises to improve cropmark detection in buried archaeological contexts. The research focuses on the Vignale plateau, part of the pre-Roman city of Falerii (Viterbo, Italy), where traditional remote sensing methods face challenges due to complex environmental and archaeological conditions. …”
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Adaptive distributed honeypot detection network for enhanced cybersecurity against DoS and DDoS attacks by V. Selva Kumar, K.R. Mohan Raj, S. Gopalakrishnan, G. Vennila, D. Dhinakaran, P. Kavitha

“…Traditional detection techniques often fall short in addressing the complexities posed by dynamic traffic patterns, diverse attack types, and real-time processing demands. …”
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Visual impairment prevention by early detection of diabetic retinopathy based on stacked auto-encoder by Shagufta Almas, Fazli Wahid, Sikandar Ali, Ahmed Alkhyyat, Kamran Ullah, Jawad Khan, Youngmoon Lee

“…While various computer-aided systems have been developed to assist in DR detection, there remains a need for accurate and efficient methods to classify its stages. …”
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The Role of Sensor Technologies in Estrus Detection in Beef Cattle: A Review of Current Applications by Inga Merkelytė, Artūras Šiukščius, Rasa Nainienė

“…To enhance reproductive efficiency, advanced technologies are increasingly being integrated into cattle management. …”
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Research on the Forward Simulation and Intelligent Detection of Defects in Highways Using Ground-Penetrating Radar by Pengxiang Li, Mingzhou Bai, Xin Li, Chenyang Liu

“…Evaluation metrics such as precision, recall, F1-score, average precision (AP), and mean average precision (mAP) were used to assess the detection efficiency and accuracy for subgrade defect images. …”
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Research on detection and tracking methods of unmanned ship water targets based on light vision by LIU Yibo, QIU Xinyu, WANG Tianhao, GAOYAN Xiusong, WANG Yintao

“…This study explores technical methods based on light vision to address the problem of target detection and tracking by surface unmanned ships in complex environments. …”
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Passive indoor human daily behavior detection method based on channel state information by Xiaochao DANG, Yaning HUANG, Zhanjun HAO, Xiong SI

“…The daily behavior detection of indoor human based on CSI is developing rapidly in the field of WSN.At present,most of the research is still in the environment of 2.4 GHz,so the detection rate,robustness and overall performance still need to be improved.In order to solve this problem,a passive indoor human behavior detection method HDFi (Human Detection with Wi-Fi) based on CSI signal was proposed.The method was used to detect the indoor human daily behavior in a 5 GHz band environment,which was divided into three steps:data acquisition,data processing,feature extraction,online detection.Firstly,the experiment collected typical daily behavioral data in complex laboratory and relatively empty meeting room.Secondly,the amplitude and phase data with more obvious features were extracted and processed by low-pass filtering to obtain a set of stable and noise-free data,and then the fingerprint database was established effectively.Finally,in the real-time detection stage,the collected data features were classified by SVM algorithm to extract more stable eigenvalues,and a classification model of indoor human daily behavior detection was established,and then matched the data in the fingerprint database.The experimental results show that the proposed method has the characteristics of high efficiency,high precision and good robustness,and the method does not need any testing personnel to carry any electronic equipment,so it has high practicability.…”
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YOLO-SRMX: A Lightweight Model for Real-Time Object Detection on Unmanned Aerial Vehicles by Shimin Weng, Han Wang, Jiashu Wang, Changming Xu, Ende Zhang

“…YOLO-SRMX demonstrates an exceptional trade-off between detection accuracy and operational efficiency, thereby underscoring its considerable potential for efficient and precise object detection on resource-constrained UAV platforms.…”
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Detecting Fraudulent Transactions for Different Patterns in Financial Networks Using Layer Weigthed GCN by Shaziya Islam, Gagan Raj Gupta, Apu Chakraborty, Santosh Singh, Anisha Soni, Chhavi Patle

“…Additionally, the flexible architecture of LayerWeighted-GCN enhances its ability to model complex financial relationships, improving fraud detection accuracy and robustness. …”
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Explainable one-class feature extraction by adaptive resonance for anomaly detection in quality assurance. by Hootan Kamran, Dionne Aleman, Chris McIntosh, Tom Purdie

“…We introduce a novel one-class classification framework, using an adaptive neural network architecture, that outperforms both traditional binary and standard one-class classification methods in this imbalanced and complex context, despite the inherent disadvantage of not learning from unacceptable plans. …”
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PERE: Prior-Enhanced and Resolution-Extended Object Detection for Industrial Laminated Panel Scenes by Haoyu Wang, Yiqiang Wu, Jinshuo Liang, Xie Xie

“…Laminated panels are widely used in industry, and their quality inspection has traditionally relied on manual labor, which is time-consuming and prone to errors. Automated detection can significantly improve efficiency and reduce human error. …”
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Citrus Disease Detection Based on Dilated Reparam Feature Enhancement and Shared Parameter Head by Xu Guo, Xingmeng Wang, Wenhao Zhu, Simon X. Yang, Lepeng Song, Ping Li, Qinzheng Li

“…Current models struggle with accuracy and efficiency due to diverse leaf lesion patterns and complex orchard environments. …”
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Aero-Engine Blade Defect Detection: A Systematic Review of Deep Learning Models by Yusra Abdulrahman, M. A. Mohammed Eltoum, Abdulla Ayyad, Brain Moyo, Yahya Zweiri

“…This is the first systematic review of deep learning models for aero-engine blade defect detection. The findings of this review demonstrate the potential of deep learning in detecting blade defects and improving the accuracy and efficiency of visual inspection. …”
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Adaptive Fusion of LiDAR Features for 3D Object Detection in Autonomous Driving by Mingrui Wang, Dongjie Li, Josep R. Casas, Javier Ruiz-Hidalgo

“…However, traditional early or late fusion methods face challenges such as high bandwidth and computational resources, which make it difficult to balance data transmission efficiency with the accuracy of perception of the surrounding environment, especially for the detection of smaller objects such as pedestrians. …”
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Mitosis detection in histopathological images using customized deep learning and hybrid optimization algorithms. by Afnan M Alhassan, Nouf I Altmami

“…Identifying mitosis is crucial for cancer diagnosis, but accurate detection remains difficult because of class imbalance and complex morphological variations in histopathological images. …”
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Spatial features of CO2 for occupancy detection in a naturally ventilated school building by Qirui Huang, Marc Syndicus, Jérôme Frisch, Christoph van Treeck

“…Accurate occupancy information helps to improve building energy efficiency and occupant comfort. Occupancy detection methods based on CO2 sensors have received attention due to their low cost and low intrusiveness. …”
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