Anomaly Detection of Liquid Level in Mold during Continuous Casting by Using Forecasting and Error Generation by Xiaojun Wu, Hongjia Kang, Sheng Yuan, Wenze Jiang, Qi Gao, Jinzhou Mi

Subjects: “…anomaly detection of liquid level in mold…”
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Detecting Cyberattacks on Electrical Storage Systems through Neural Network Based Anomaly Detection Algorithm by Giovanni Battista Gaggero, Roberto Caviglia, Alessandro Armellin, Mansueto Rossi, Paola Girdinio, Mario Marchese

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An Efficient and Robust Unsupervised Anomaly Detection Method Using Ensemble Random Projection in Surveillance Videos by Jingtao Hu, En Zhu, Siqi Wang, Xinwang Liu, Xifeng Guo, Jianping Yin

Subjects: “…video anomaly detection…”
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Enhancing Anomaly Detection Models for Industrial Applications through SVM-Based False Positive Classification by Ji Qiu, Hongmei Shi, Yuhen Hu, Zujun Yu

Subjects: “…anomaly detection…”
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MST-VAE: Multi-Scale Temporal Variational Autoencoder for Anomaly Detection in Multivariate Time Series by Tuan-Anh Pham, Jong-Hoon Lee, Choong-Shik Park

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A Dataset Fusion Algorithm for Generalised Anomaly Detection in Homogeneous Periodic Time Series Datasets by Ayman Elhalwagy, Tatiana Kalganova

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Hyperspectral Anomaly Detection via Dual Dictionaries Construction Guided by Two-Stage Complementary Decision by Sheng Lin, Min Zhang, Xi Cheng, Liang Wang, Maiping Xu, Hai Wang

Subjects: “…hyperspectral anomaly detection…”
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Machine Learning-Based Anomaly Detection Using K-Mean Array and Sequential Minimal Optimization by Saad Gadal, Rania Mokhtar, Maha Abdelhaq, Raed Alsaqour, Elmustafa Sayed Ali, Rashid Saeed

Subjects: “…anomaly detection…”
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Advancements of Data Anomaly Detection Research in Wireless Sensor Networks: A Survey and Open Issues by Mohd Aizaini Maarof, Murad A. Rassam, Anazida Zainal

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Bridge management through digital twin-based anomaly detection systems: A systematic review by Alejandro Jiménez Rios, Vagelis Plevris, Maria Nogal

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Industrial Product Surface Anomaly Detection with Realistic Synthetic Anomalies Based on Defect Map Prediction by Tao Peng, Yu Zheng, Lin Zhao, Enrang Zheng

“…Among image-based anomaly detection, reconstruction-based methods are the most commonly used. …”
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CLDTLog: System Log Anomaly Detection Method Based on Contrastive Learning and Dual Objective Tasks by Gaoqi Tian, Nurbol Luktarhan, Haojie Wu, Zhaolei Shi

Subjects: “…log anomaly detection…”
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Extracellular Vesicle Protein Expression in Doped Bioactive Glasses: Further Insights Applying Anomaly Detection by Mauro Nascimben, Hugo Abreu, Marcello Manfredi, Giuseppe Cappellano, Annalisa Chiocchetti, Lia Rimondini

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Power Consumption Predictive Analytics and Automatic Anomaly Detection Based on CNN-LSTM Neural Networks by Arif Irwansyah, Effry Muhammad, Firman Arifin, Budi Nur Iman, Hendhi Hermawan

Subjects: “…anomaly detection…”
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A Generalized Wind Turbine Anomaly Detection Method Based on Combined Probability Estimation Model by Xiangjun Zeng, Ming Yang, Chen Feng, Yaohua Tang

Subjects: “…Anomaly detection…”
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Protection of Superconducting Industrial Machinery Using RNN-Based Anomaly Detection for Implementation in Smart Sensor by Maciej Wielgosz, Andrzej Skoczeń, Ernesto De Matteis

Subjects: “…anomaly detection…”
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Smart Aging System: Uncovering the Hidden Wellness Parameter for Well-Being Monitoring and Anomaly Detection by Hemant Ghayvat, Muhammad Awais, Sharnil Pandya, Hao Ren, Saeed Akbarzadeh, Subhas Chandra Mukhopadhyay, Chen Chen, Prosanta Gope, Arpita Chouhan, Wei Chen

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A Spatio‐Temporal Enhanced Graph‐Transformer AutoEncoder embedded pose for anomaly detection by Honglei Zhu, Pengjuan Wei, Zhigang Xu

“…Abstract Due to the robustness of skeleton data to human scale, illumination changes, dynamic camera views, and complex backgrounds, great progress has been made in skeleton‐based video anomaly detection in recent years. The spatio‐temporal graph convolutional network has been proven to be effective in modelling the spatio‐temporal dependencies of non‐Euclidean data such as human skeleton graphs, and the autoencoder based on this basic unit is widely used to model sequence features. …”
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Deep Autoencoder-Based Integrated Model for Anomaly Detection and Efficient Feature Extraction in IoT Networks by Khaled A. Alaghbari, Heng-Siong Lim, Mohamad Hanif Md Saad, Yik Seng Yong

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Machine-Learning-Based Modeling of a Hydraulic Speed Governor for Anomaly Detection in Hydropower Plants by Mehmet Akif Bütüner, İlhan Koşalay, Doğan Gezer

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