Discriminative Unsupervised Feature Learning with Exemplar Convolutional Neural Networks.

IEEE Transactions on Pattern Analysis and Machine Intelligence(2016)

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摘要
Deep convolutional networks have proven to be very successful in learning task specific features that allow for unprecedented performance on various computer vision tasks. Training of such networks follows mostly the supervised learning paradigm, where sufficiently many input-output pairs are required for training. Acquisition of large training sets is one of the key challenges, when approaching a...
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关键词
Training,Accuracy,Feature extraction,Neural networks,Image color analysis,Support vector machines,Unsupervised learning
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