Figure 3.


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Comparison between closed set and open set problem. Figure 3a demonstrates the distribution of original dataset including 4 known classes (KC) and 2 unknown classes (UC). Figure 3b shows the traditional solution to closed set problem, where the decision boundary is learned and utilized to classify KCs without considering UCs. Figure 3c illustrates open set identification, where the decision boundary either limits the whole scope of KCs to accomplish a two-class classification problem (also known as anomaly detection) or distinguishes among all the KCs and rejects UCs

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