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The state of classifier incongruence in decision making systems incorporating multiple classifiers is often an indicator of anomaly caused by an unexpected observation or an unusual situation. Its assessment is important as one of the key mechanisms for domain anomaly detection. In this paper, we investigate the sensitivity of Delta divergence, a novel measure of classifier incongruence, to estimation...
Face spoofing detection is commonly formulated as a two-class recognition problem where relevant features of both positive (real access) and negative samples (spoofing attempts) are utilized to train the system. However, the diversity of spoofing attacks, any new means of spoofing attackers, may invent (previously unseen by the system) the problem of imaging sensor interoperability, and other environmental...
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