USING SUPPORT VECTORS TO BUILD A RULE-BASED SYSTEM FOR DETECTING MALICIOUS PROCESSES IN AN ORGANISATION'S NETWORK TRAFFIC by Halyna Haidur, Sergii Gakhov, Dmytro Hamza

“… The growing complexity and sophistication of cyberattacks on organisational information resources and the variety of malware processes in unprotected networks necessitate the development of advanced methods for detecting malicious processes in network traffic. …”
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AI-based orchard monitoring at night: Enhancing sustainable fruit production through real-time apple detection by Kutyrev Alexey, Khort Dmitry, Smirnov Igor, Zubina Valeria

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Intelligent GPR Detection of Backfill Grouting Quality and Adjacent Soil Cavities in Shield Tunnels: A Case Study by Guangyuan Cai, Xiongyao Xie, Kang Li

“…This research advances the automation and intelligence of backfill grouting and cavity detection, supporting the safe and efficient progress of shield tunnel construction.…”
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Temporal Pyramid Alignment and Adaptive Fusion of Event Stream and Image Frame for Keypoint Detection and Tracking in Autonomous Driving by Peijun Shi, Chee-Onn Chow, Wei Ru Wong

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PIFR: A novel approach for analyzing pose angle-based human activity to automate fall detection in videos. by Vungsovanreach Kong, Saravit Soeng, Munirot Thon, Wan-Sup Cho, Anand Nayyar, Tae-Kyung Kim

“…The method outperforms existing approaches by effectively capturing complex geometric changes during fall events. The system is applicable to smart homes, wearable devices, and healthcare monitoring platforms, offering a scalable, reliable, and efficient solution to enhance safety and independence for elderly individuals, thereby contributing to advancements in health-monitoring technology.…”
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Approach for enhancing the accuracy of semantic segmentation of chest X-ray images by edge detection and deep learning integration by Lesia Mochurad

“…These results consistently outperform the baseline U-net model without edge enhancement.DiscussionThe integration of contour detection methods with the U-net model significantly improves the segmentation quality of complex anatomical regions in chest X-rays. …”
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Toward Automatic Streetside Building Identification With an Integrated YOLO Model for Building Detection and a Vision Transformer for Identification by Ossama Krawi, Lavdie Rada

“…Utilizing Google Street View datasets that cover entire urban landscapes, the proposed method offers efficiency and scalability, simplifying data acquisition and avoiding logistical complexities of manual interaction for targeted collections. …”
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A new statistical metric for robust target detection in cryo-EM using 2D template matching by Kexin Zhang, Pilar Cossio, Aaditya V. Rangan, Bronwyn A. Lucas, Nikolaus Grigorieff

“…In this work, a novel 2DTM metric, referred to as the 2DTM p-value, is developed to extend the 2DTM framework to more complex applications. The 2DTM p-value combines information from two previously used 2DTM metrics, namely the 2DTM signal-to-noise ratio (SNR) and z-score, which are derived from the cross-correlation coefficient between the target and the template. …”
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Millimeter-Wave Reflectometry for Detecting Graphite Contamination in Titanium (Ti64) Powder Used in Additive Manufacturing (AM) by Jayaram Kizhekke Pakkathillam, Jessica Haack, Reza Zoughi

“…Titanium (Ti64) alloys are extensively used for additive manufacturing (AM) of complex and critical parts in the aerospace industry. …”
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Lightweight YOLOv8 for tongue teeth marks and fissures detection based on C2f_DCNv3 by Chunyang Jin, Delong Zhang, Xiyuan Cao, Zhidong Zhang, Chenyang Xue, Yanjun Zhang

“…Additionally, the model reduces computational cost by approximately one-third in terms of FLOPS, maintaining high accuracy while greatly decreasing the number of parameters, thus offering a more robust and resource-efficient solution. For tongue crack detection, the mAP increases to 91.34%, with notable improvements in F1 score, precision, and recall. …”
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Semi-Supervised Anomaly Detection for the Identification of Damages in an Aerospace Sandwich Structure Based on Synthetically Generated Strain Data by Florian Forsthuber, Christoph Kralovec, Martin Schagerl

“…In this field, machine learning (ML) techniques are attracting growing attention due to their capability to recognize complex patterns, making them very suitable for the identification of damages in operating mechanical structures. …”
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A High Accuracy and Large-Scale Detection for Fixed-Wing UAV Autonomous Ground Landing With GNSS-Denied by Bin Fang, Zhiwei Zhong, Xiangjun Jiang

“…To further facilitate large-scale range detection in GNSS-denied conditions, a landing guidance window is developed, enabling the efficient search for and tracking of UAVs. …”
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SDKU-Net: A Novel Architecture with Dynamic Kernels and Optimizer Switching for Enhanced Shadow Detection in Remote Sensing by Gilberto Alvarado-Robles, Isac Andres Espinosa-Vizcaino, Carlos Gustavo Manriquez-Padilla, Juan Jose Saucedo-Dorantes

“…To address these issues, this study proposes the Supervised Dynamic Kernel U-Net (SDKU-Net), a novel architecture designed to enhance shadow detection in complex remote sensing scenarios. SDKU-Net integrates dynamic kernel adjustment, a combined loss function incorporating Focal and Tversky Loss, and optimizer switching to effectively tackle class imbalance and improve segmentation quality. …”
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Electrochemical Immunosensor Using COOH-Functionalized 3D Graphene Electrodes for Sensitive Detection of Tau-441 Protein by Sophia Nazir, Muhsin Dogan, Yinghui Wei, Genhua Pan

“…Early diagnosis of Alzheimer’s disease (AD) is essential for effective treatment; however current diagnostic methods are often complex, costly, and unsuitable for point-of-care testing. …”
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Development of a Fully Automated Microfluidic Electrochemical Sensor on the ESSENCE Platform for Rapid Detection of Single-Stranded DNA by Niranjan Haridas Menon, Maryom Rahman, Sagnik Basuray

“…This study presents a fully automated microfluidic electrochemical sensor for the detection of single-stranded DNA (ssDNA) on the ESSENCE platform. …”
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YOLO-AMM: A Real-Time Classroom Behavior Detection Algorithm Based on Multi-Dimensional Feature Optimization by Yi Cao, Qian Cao, Chengshan Qian, Deji Chen

“…However, the existing models are still deficient in detail feature capture capability, multi-layer feature correlation, and multi-scale target adaptability, making it challenging to realize high-precision real-time detection in complex scenes. This paper proposes an improved classroom behavior detection algorithm, YOLO-AMM, to solve these problems. …”
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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 ML models, especially complex ones like Random Forest, require substantial processing power, which necessitates efficient data handling and possibly leveraging edge computing resources to reduce latency. …”
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Novel Europium-Grafted 3D Covalent Organic Framework for Selective and Sensitive Fluorescence-Enhanced Detection of Levofloxacin by Junyi Zhao, Chao Zhang, Zhijie Qiu, Zerong Zhang, Xiaorou Lin, Shibin Huang, Jianfeng Zhang, Jingpeng Wu, Li Liao, Rui Wang

“…Levofloxacin (LVFX), a fluoroquinolone antibacterial agent widely used in treating bacterial infections, poses significant risks when overused, necessitating the development of reliable and efficient detection methods. Herein, we introduce Eu@SUZ−103, a novel europium-grafted three-dimensional covalent organic framework (COF) featuring an eight-connected <b><i>bcu</i></b> net, for the selective detection of LVFX in serum and urine. …”
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Portable Fluorescence Microarray Reader-Enabled Biomarker Panel Detection System for Point-of-Care Diagnosis of Lupus Nephritis by Aygun Teymur, Iftak Hussain, Chenling Tang, Ramesh Saxena, David Erickson, Tianfu Wu

“…However, many POC systems lack the sensitivity or multiplexing capability required for complex diseases. This study introduces an LED-based fluorescence reader designed for POC applications, enabling multiplex detection of lupus nephritis (LN) biomarkers using a biomarker microarray (BMA) slide. …”
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Deep learning for rice leaf disease detection: A systematic literature review on emerging trends, methodologies and techniques by Chinna Gopi Simhadri, Hari Kishan Kondaveeti, Valli Kumari Vatsavayi, Alakananda Mitra, Preethi Ananthachari

“…Machine learning techniques are used to detect diseases based on the extracted features. In contrast, deep learning techniques learn complex patterns from large datasets without explicit feature extraction techniques and are well-suited for disease detection tasks. …”
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