Malicious Traffic Detection on Tofino Using Graph Attention Model by Xichang Gao, Lizhuang Tan, Shengpeng Chen, Peiying Zhang, Jian Wang

“…With the surge of malicious traffic in networks, existing detection methods struggle to balance real-time performance and efficiency. …”
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A Portable Optical Sensor for Microplastic Detection: Development and Calibration by Maximiliano Campos-López, Ricardo Aguilar-Garay, Dafne E. González-Rodriguez, Verónica I. Mejía-Lopez, Margoth M. Gamboa-Lugo, Vicente Garibay-Febles, Marco A. Reyes-Guzmán, Álvaro Gordillo-Sol, Jorge A. Mendoza-Pérez

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Fast horizon detection in maritime images using region-of-interest by Chi Yoon Jeong, Hyun S Yang, KyeongDeok Moon

“…However, these methods suffer from high processing times, requiring tens of seconds to complete horizon detection. …”
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Improving detectability of illegal fishing activities across supply chains by Rodrigo Oyanedel, Stefan Gelcich, E. J. Milner-Gulland, Chris Wilcox

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High-Precision Chip Detection Using YOLO-Based Methods by Ruofei Liu, Junjiang Zhu

“…This lightweight and efficient approach is particularly effective in detecting small-scale objects within images and accurately analyzing dynamic debris in video sequences, providing a robust solution for automated debris monitoring in machine tool processing applications.…”
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Machine vision-based automatic fruit quality detection and grading by Amna, Muhammad Waqar AKRAM, Guiqiang LI, Muhammad Zuhaib AKRAM, Muhammad FAHEEM, Muhammad Mubashar OMAR, Muhammad Ghulman HASSAN

“…The prototype consisted of defective fruit detection and mechanical sorting systems. Image processing algorithms and deep learning frameworks were used for detection of defective fruit. …”
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Multiclass Evaluation of Vision Transformers for Industrial Welding Defect Detection by Antonio Contreras Ortiz, Ricardo Rioda Santiago, Daniel E. Hernandez, Miguel Lopez-Montiel

“…While welding tasks are frequently automated, inspection processes remain largely manual. Advances in computer vision and AI, especially ViTs, now enable more effective defect detection and classification, offering opportunities to automate these workflows. …”
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Indirect detection constraints on semi-annihilation of inert scalar multiplets by Hugues Beauchesne, Cheng-Wei Chiang

“…The existence of these processes can alleviate certain constraints and substantially modify the indirect detection signal. …”
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Improving Threat Detection in Wazuh Using Machine Learning Techniques by Samir Achraf Chamkar, Mounia Zaydi, Yassine Maleh, Noreddine Gherabi

“…Real-time deployment requirements are rigorously evaluated, with all models maintaining end-to-end processing latencies below 100 milliseconds and 95% of events processed within 500 milliseconds. …”
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Methods to detect avian influenza virus for food safety surveillance by Ping SHI, Shu Geng, Ting-ting LI, Yu-shui LI, Ting FENG, Hua-nan WU

“…Conventional methods usually applied for the purpose of AI diagnosis face some practical challenges to establishing a comprehensive poultry surveillance program in the poultry supply chain. Diverse development of new technologies can meet the specific requirements of AI virus detection in various stages or scenarios throughout the poultry supply chain where onsite, rapid and ultrasensitive methods are emphasized. …”
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Leveraging multivariate information for community detection in functional brain networks by Maria Grazia Puxeddu, Maria Pope, Thomas F. Varley, Joshua Faskowitz, Olaf Sporns

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An Innovative Multiparametric Sensor Design for Detecting Microplastics and Heavy Metals by Ekrem Kursad Dal, Adem Gunes, Recai Kilic

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Toward Causal and Evidential Open-Set Temporal Action Detection by Zhuoyao Wang, Rui-Wei Zhao, Rui Feng, Cheng Jin

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Concept Drift Detection Based on Deep Neural Networks and Autoencoders by Lisha Hu, Yaru Lu, Yuehua Feng

“…In domains such as fraud detection, healthcare, and industrial equipment maintenance, streaming data often exhibit characteristics such as continuous generation, high real-time processing requirements, and complex distributions, making it susceptible to concept drift. …”
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Evaluating the Performance of SVM, Isolation Forest, and DBSCAN for Anomaly Detection by Lu Haowen

“…With the advancement of computer technologies, various data models and algorithms have been integrated into industrial processes, significantly improving the efficiency of anomaly detection in datasets while reducing time and energy consumption. …”
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Detection of smoke from infrared image frames in the aircraft cargoes by Li Deng, Qian Chen, Yuanhua He, Xiubao Sui, Qin Wang

“…Since, in the cargo of civil aircraft, visible image processing technology cannot be used to detect smoke in the event of a fire due to the closed dark environment, a novel smoke detection method using infrared image processing technology is presented. …”
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Dynamics of the island mass effect – Part 1: Detecting the extent by G. Bourdin, L. Karp-Boss, L. Karp-Boss, F. Lombard, G. Gorsky, E. Boss

“…<p>In the vast Pacific Ocean, remote islands and atolls induce mesoscale and sub-mesoscale processes that significantly impact the surrounding oligotrophic ocean, collectively referred to as the island mass effect (IME). …”
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Comparison of bluetongue virus detection and quantitation methods in south India by Subhra Subhadra, Subrat Kumar, Veluvarthy VS Suryanarayana, Daggupati Sreenivasulu

“…Polymerase chain reaction (PCR)-based real-time detection assays may be an ideal method to detect the BTV genome in animal blood at an early stage of infection. …”
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Code vulnerability detection method based on graph neural network by Hao CHEN, Ping YI

“…The schemes of using neural networks for vulnerability detection are mostly based on traditional natural language processing ideas, processing the code as array samples and ignoring the structural features in the code, which may omit possible vulnerabilities.A code vulnerability detection method based on graph neural network was proposed, which realized function-level code vulnerability detection through the control flow graph feature of the intermediate language.Firstly, the source code was compiled into an intermediate representation, and then the control flow graph containing structural information was extracted.At the same time, the word vector embedding algorithm was used to initialize the vector of basic block to extract the code semantic information.Then both of above were spliced to generate the graph structure sample data.The multilayer graph neural network model was trained and tested on graph structure data features.The open source vulnerability sample data set was used to generate test data to evaluate the method proposed.The results show that the method effectively improves the vulnerability detection ability.…”
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Optical Differentiation and Edge Detection Based on Birefringence of Uniaxial Crystals by Xu Chen, Ping Huang, Xuan Tang, Xunong Yi

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