Probability Models for Open Set Recognition
نویسندگان
چکیده
منابع مشابه
Multi-class Open Set Recognition Using Probability of Inclusion
The perceived success of recent visual recognition approaches has largely been derived from their performance on classification tasks, where all possible classes are known at training time. But what about open set problems, where unknown classes appear at test time? Intuitively, if we could accurately model just the positive data for any known class without overfitting, we could reject the larg...
متن کاملSupplemental Material: Multi-Class Open Set Recognition Using Probability of Inclusion
In this supplemental material we present additional plots that are meant to add to the reader’s understanding of the open set recognition problem and our solution. We start with a look at SVM decision surfaces, and then offer a discussion of the difference in observed performance when Accuracy or F-measure is reported as an evaluation statistic. We also provide plots showing performance with al...
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This set of notes will cover basic concepts in multivariate probability models, i.e., probability models involving multiple random variables. We will begin by discussing the important concepts of independence and conditional independence and then look at the general framework of graphical models. We will then look at specific examples of models: for joint distributions we will look at the naive...
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Open set recognition problems exist in many domains. For example in security, new malware classes emerge regularly; therefore malware classication systems need to identify instances from unknown classes in addition to discriminating between known classes. In this paper we present a neural network based representation for addressing the open set recognition problem. In this representation insta...
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ژورنال
عنوان ژورنال: IEEE Transactions on Pattern Analysis and Machine Intelligence
سال: 2014
ISSN: 0162-8828,2160-9292
DOI: 10.1109/tpami.2014.2321392