Low-Cost Active Anomaly Detection with Switching Latency by Fengfan Qin, Hui Feng, Tao Yang, Bo Hu

Subjects: “…anomaly detection…”
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Event-Based Anomaly Detection for Searches for New Physics by Sergei Chekanov, Walter Hopkins

Subjects: “…anomaly detection…”
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Similarity matrix-based anomaly detection for clinical intervention by Ryan D’Mello, Jennifer Melcher, John Torous

“…These computed measures can then be used for anomaly detection, baseline routine computation, and trajectory clustering. …”
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Autoencoder-Like Knowledge Distillation Network for Anomaly Detection by Caie Xu, Bingyan Wang, Dandan Ni, Jin Gan, Mingyang Wu, Wujie Zhou

Subjects: “…Anomaly detection…”
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Augmenting anomaly detection for autonomous vehicles with symbolic rules by Chen, Tianye,M.EngMassachusetts Institute of Technology.

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Machine learning for automated anomaly detection in semiconductor manufacturing by DeLaus, Michael Daniel.

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ELITE: Robust Deep Anomaly Detection with Meta Gradient by Zhang, Huayi, Cao, Lei, VanNostrand, Peter, Madden, Samuel, Rundensteiner, Elke A

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Anomaly Detection in Collider Physics via Factorized Observables by Wynne, Raymond

“…This goal has motivated the use of machine learning for unsupervised anomaly detection. In this paper, we introduce a new anomaly detection strategy called FORCE: factorized observables for regressing conditional expectations. …”
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Developing Pattern and Anomaly Detection Methods in Influence Campaigns by Mitchell, William B.

“…This project seeks to expand on the previous work of Group 52 on GIM, incorporating pattern and anomaly detection methods. Several statistical and machine learning methods were applied to a data set of approximately 30,000 news articles from a 2-year period between August 2019 and August 2021. …”
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Anomaly detection in brain connectivity structure : an application to epilepsy by Sweet, Andrew (Andrew Douglas)

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Time series clustering and anomaly detection in the financial markets by Lim, Wilbur Yong Wei

“…Time series clustering and anomaly detection provide researches with useful domain insights but are also two of the most challenging time series data mining issues. …”
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An incremental clustering method for anomaly detection in flight data by Zhao, Weizun, Li, Lishuai, Alam, Sameer, Wang, Yanjun

“…Safety is a top priority for civil aviation. New anomaly detection methods, primarily clustering methods, have been developed to monitor pilot operations and detect any risks from such flight data. …”
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Anomaly detection in smart grids using machine learning by Li, Xiang

“…In this dissertation, anomaly detection strategies based on reinforcement learning (RL) are proposed. …”
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Anomaly detection for industrial parts using PatchCore by Kuah, Zheng Xuan

“…The decision of an anomaly detection revolves around a binary problem. This paper will delve into a state-of-the-art method of anomaly detection known as PatchCore and its effectiveness on various datasets. …”
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Event recognition and anomaly detection using machine learning by Peng, Xinggan

“…Abnormal event recognition and anomaly detection aim to discover incidents, patterns or objects that do not conform to expected behaviour. …”
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Anomaly detection for X-ray of PCB & IC images by Heng, Daryl Ew-Jynn

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Anomaly detection in gas pipelines using flow and pressure by Kumar, Abhishek

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Anomaly detection using pattern-of-life visual metaphors by Happa, J, Bashford-Rogers, T, Agrafiotis, I, Goldsmith, M, Creese, S

“…Similar to other anomaly-detection techniques, false positives do exist in our general approach as well. …”

Anomaly detection in networks with application to financial transaction networks by Elliott, A, Cucuringu, M, Luaces, M, Reidy, P, Reinert, G

“…We compare our method with Oddball, a widely used method for anomaly detection in networks, as well as to random classification. …”

Packet header anomaly detection using statistical analysis by Yassin, Warusia, Udzir, Nur Izura, Abdullah, Azizol, Abdullah @ Selimun, Mohd Taufik, Muda, Zaiton, Zulzalil, Hazura

“…The disclosure of network packets to recurrent cyber intrusion has upraised the essential for modelling various statistical-based anomaly detection methods lately. Theoretically, the statistical-based anomaly detection method fascinates researcher’s attentiveness, but technologically, the fewer intrusion detection rates persist as vulnerable disputes. …”