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FLAIRS
2007

Knowledge Transfer in Deep Convolutional Neural Nets

9 years 4 months ago
Knowledge Transfer in Deep Convolutional Neural Nets
Knowledge transfer is widely held to be a primary mechanism that enables humans to quickly learn new complex concepts when given only small training sets. In this paper, we apply knowledge transfer to deep convolutional neural nets, which we argue are particularly well suited for knowledge transfer. Our initial results demonstrate that components of a trained deep convolutional neural net can constructively transfer information to another such net. Furthermore, this transfer is completed in such a way that one can envision creating a net that could learn new concepts throughout its lifetime.
Steven Gutstein, Olac Fuentes, Eric Freudenthal
Added 02 Oct 2010
Updated 02 Oct 2010
Type Conference
Year 2007
Where FLAIRS
Authors Steven Gutstein, Olac Fuentes, Eric Freudenthal
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