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Detecting unusual or abnormal patterns in data is one of the common tasks of AI algorithms in commercial applications. In some applications, such as fraud detection, defect detection or medical diagnostics, anomaly detection is the main objective. In other applications, detecting abnormal data points is part of the data cleaning and preparation pipeline. In all cases, the use of AI-based methods relies on having a training dataset which can represent the normal behaviour, and must therefore be free of anomalies. Problems arise when we realize that having an anomaly-free training dataset is not always possible in practice: most real-world datasets are contaminated with unknown anomalies or mislabeled data..

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2024.

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Lone, Omar; Doran, Hans Dermot,

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Veljanovska, Suzana; Doran, Hans Dermot,

2024.

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Tordoya Taquichiri, Carlos Rafael; Ganz, David; Buchheim, Klaus,

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Reconfigurable hardware revisited : implementing an optimised AI pipeline on the HPDP processor.

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Doran, Hans Dermot,

2024.

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2024.

Trust me if you can : practical challenges affecting the integration of carpooling in Mobility-as-a-Service platforms.

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2024.

MathNet : a data-centric approach for printed mathematical expression recognition.

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2024.

Probabilistic U-Net model observer for the DDC method in CT scan protocol optimization.

Physics in Medicine & Biology.

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Brunner, Kilian; Da Silva Miranda, Luis; Ostertag, Martin,

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Gür, Gürkan; Porambage, Pawani; Osorio, Diana Moya; Yavuz, Attila A.; Liyanage, Madhusanka,

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6G security vision : a concise update [paper].

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Unveiling the synergy : economic and environmental value of building management systems in the era of digital service innovation [paper].

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Baumgartner, Corinna; Helmers, Eckard,

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Life cycle assessment of electric kick scooters : consolidating environmental impact quantification and concluding climate-friendly use options.

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Morgese, Giulia; Siegmann, Konstantin; Winkler, Martin,

2024.

Specific, nondestructive, and durable adhesion primer for polyolefins.

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2024.

Automated and orchestrated CI/CD pipelines in industrial protocol certification testing [paper].

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Bypassing security measures with voltage fault injection on Cortex-M devices.

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Gerber, Jonathan; Saxer, Jasmin S.; B. Kreiner, Bruno; Weiler, Andreas,

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DIGILOG : towards a monitoring platform for digital transformation of European communities.

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RWTH Aachen University.

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Exploring the relationship between behavioral and neurological impairments due to mild cognitive impairment : correlation study between virtual kiosk test and EEG-SSVEP.

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Identifying safety–critical concerns in unmanned aerial vehicle software platforms with SALIENT.

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