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Novelty detection

3 open-access journal articles on novelty detection, published in 2026 in Life of Research. Every record is free to read and download, with a permanent link and a ready-made citation.

3 records

Journal article

Detectors Say 'Different', Not 'What': Score, Deviation and Name Are Three Claims With Three Referees, Only the Name Needs a Referee Outside the Detector, and Published Results Show Novelty Detected Far More Reliably Than It Is Named

An anomaly or novelty detector reports that an input is unlike the data it was built from. Users want more: they want to know what the unusual thing is. Explainable anomaly detection is often presented as supplying that second answer, but three different claims travel under the one word…

Cite Related research LOR-00085 · 9 views · 15 downloads
PDF388 KB

Journal article

Drift or New Class? Without Labels a Drifted Class and a New One Can Produce the Same Stream, the Two Lines of Work With the Most Explicit Assumptions Each Get an Answer by Freezing the Variable the Other Lets Move, and No Located Benchmark Scores the Attribution

A classifier deployed on a stream eventually sees inputs its model does not explain. Two different events can produce them: a known class can have drifted, or a class that did not exist in training can have appeared. The stream-mining literature treats these as separate problems, concept drift and…

Cite Related research LOR-00069 · 35 views · 16 downloads
PDF408 KB

Journal article

A Failure to Reject Is Not a Finding: Closed-Set Accuracy, Specialized Open-Set Recognition, and the Semantic-Distance Parameter the Deflationary Debate Leaves Free

A widely cited result reports that the open-set performance of an image classifier is strongly correlated with its closed-set accuracy, and that a well-trained baseline scoring rule is competitive with specialized open-set machinery. The result is often read as showing that specialized open-set…

Cite Related research LOR-00015 · 7 views · 20 downloads
PDF509.1 KB

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