Nanopublications

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@prefix dct: <http://purl.org/dc/terms/> .
@prefix nt: <https://w3id.org/np/o/ntemplate/> .
@prefix npx: <http://purl.org/nanopub/x/> .
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@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .
@prefix orcid: <https://orcid.org/> .
@prefix prov: <http://www.w3.org/ns/prov#> .
@prefix foaf: <http://xmlns.com/foaf/0.1/> .

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sub:assertion {
sub:assertion rdfs:label """Citation from the paper linked in this assertion:
Abstract:
\"On the test data, we achieved top-1 and top-5 error rates of 37.5% and 17.0% which is considerably better than the previous state-of-the-art. The neural network, which has 60 million parameters and 650,000 neurons, consists of five convolutional layers, some of which are followed by max-pooling layers, and three fully-connected layers with a final 1000-way softmax.\"

Section 3.5:
\"As depicted in Figure 2, the net contains eight layers with weights; the first five are convolutional and the remaining three are fully-connected. The output of the last fully-connected layer is fed to a 1000-way softmax which produces a distribution over the 1000 class labels.\"

Table 2:
For \"1 CNN\", the Top-5 (test) shows 16.4%, and for \"5 CNNs\", the Top-5 (test) also shows 16.4%.
""" ;
rdfs:seeAlso <https://proceedings.neurips.cc/paper_files/paper/2012/file/c399862d3b9d6b76c8436e924a68c45b-Paper.pdf> .
}

sub:provenance {
sub:assertion prov:wasAttributedTo orcid:0000-0002-1784-2920 .
}

sub:pubinfo {
 orcid:0000-0002-1784-2920 foaf:name "Anne Fouilloux" .
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 dct:license <https://creativecommons.org/licenses/by/4.0/> ;
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