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Toward Open Set Recognition

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013
To date, almost all experimental evaluations of machine learning-based recognition algorithms in computer vision have taken the form of "closed set" recognition, whereby all testing classes are known at training time. A more realistic scenario for vision applications is "open set" recognition, where incomplete knowledge of the world is present at ...
Walter J. Scheirer   +3 more
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Contrastive Open Set Recognition

Proceedings of the AAAI Conference on Artificial Intelligence, 2023
In conventional recognition tasks, models are only trained to recognize learned targets, but it is usually difficult to collect training examples of all potential categories. In the testing phase, when models receive test samples from unknown classes, they mistakenly classify the samples into known classes.
Baile Xu, Furao Shen, Jian Zhao 0013
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Generalized Open Sets

Acta Mathematica Hungarica, 1997
Various kinds of generalized open sets are studied together in this article. The author considers monotone mappings \(\gamma:\exp X\to \exp X\) (monotone in the sense that \(A\subset B\) implies \(\gamma(a)\subset \gamma(B)\)), and develops properties common to several classes of generalized open sets.
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On the topology of \(\delta_e\)-open sets

2023
Summary: The main purpose of this paper is to introduce and investigate a new class of open sets called \(\delta_e\)-open sets. For this aim, first we define and study the notion of \(e\)-regular open set via \(e\)-closure operator. Then, we introduce the notion of \(\delta_e\)-open set via \(e\)-regular open set.
lrm;Dalkiran, C.   +1 more
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