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Abstract: Novelty detection is the identification of new or unknown data or signal that a machine learning system is not aware of during training. Novelty detection is one of the fundamental requirements of a good classification or identification system since sometimes the test data contains information about objects that were not known at the time of training the model. In this paper we provide stateof -the-art review in the area of novelty detection based on statistical approaches. The second part... (Update)
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BibTeX entry: (Update)
@misc{ markou-novelty,
author = "Markos Markou and Sameer Singh",
title = "Novelty Detection: A Review - Part 1: Statistical Approaches",
url = "citeseer.ist.psu.edu/658958.html" }
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Documents on the same site (http://www.dcs.ex.ac.uk/research/pann/master/2003.htm): More
Novelty Detection: A Review - Part 2: Neural network based.. - Markou, Singh (2003) (Correct)
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On the Optimality of Image Processing Pipeline - Sameer Singh Member (Correct)
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