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{0: {'id': '01440764-n', | |
'label': 'tench, Tinca tinca', | |
'uri': 'http://wordnet-rdf.princeton.edu/wn30/01440764-n'}, | |
1: {'id': '01443537-n', | |
'label': 'goldfish, Carassius auratus', | |
'uri': 'http://wordnet-rdf.princeton.edu/wn30/01443537-n'}, | |
2: {'id': '01484850-n', | |
'label': 'great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias', | |
'uri': 'http://wordnet-rdf.princeton.edu/wn30/01484850-n'}, | |
3: {'id': '01491361-n', |
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n02119789 1 kit_fox | |
n02100735 2 English_setter | |
n02110185 3 Siberian_husky | |
n02096294 4 Australian_terrier | |
n02102040 5 English_springer | |
n02066245 6 grey_whale | |
n02509815 7 lesser_panda | |
n02124075 8 Egyptian_cat | |
n02417914 9 ibex | |
n02123394 10 Persian_cat |
##VGG16 model for Keras
This is the Keras model of the 16-layer network used by the VGG team in the ILSVRC-2014 competition.
It has been obtained by directly converting the Caffe model provived by the authors.
Details about the network architecture can be found in the following arXiv paper:
Very Deep Convolutional Networks for Large-Scale Image Recognition
K. Simonyan, A. Zisserman
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