Visualizing Transfer Learning
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Abstract: We provide visualizations of individual neurons of a deep image recognition network during the temporal process of transfer learning. These visualizations qualitatively demonstrate various novel properties of the transfer learning process regarding the speed and characteristics of adaptation, neuron reuse, spatial scale of the represented image features, and behavior of transfer learning to small data. We publish the large-scale dataset that we have created for the purposes of this analysis. Authors: Róbert Szabó, Dániel Katona, Márton Csillag, Adrián Csiszárik, Dániel Varga (Budapest University of Technology)

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