Open-set Recognition with Adversarial Autoencoders
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OSRAAE

Open-set Recognition with Adversarial Autoencoders

A deep learning approach to solving the problem of open-set recognition, by leveraging an encoder-decoder network architecture in conjunction with a multi-class classifier. The network enables learning a novelty detector that computes the probability of a sample to belong to one of the known classes versus being unknown. If known, the multi-class classifiers assigns the class label to the sample.