Interpreting Deep Visual Representations via Network Dissection

The success of recent deep convolutional neural networks (CNNs) depends on learning hidden representations that can summarize the important factors of variation behind the data. In this work, we describe Network Dissection, a method that interprets networks by providing meaningful labels to their in...

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Bibliographic Details
Main Authors: Zhou, Bolei (Author), Bau, David (Author), Oliva, Aude (Author), Torralba, Antonio (Author)
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers, 2019-11-11T18:43:22Z.
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