|
gptkbp:instanceOf
|
gptkb:convolutional_neural_network
|
|
gptkbp:activatedBy
|
gptkb:ReLU
|
|
gptkbp:arXivID
|
gptkb:1409.1556
|
|
gptkbp:citation
|
over 100,000
|
|
gptkbp:developedBy
|
gptkb:University_of_Oxford
gptkb:Visual_Geometry_Group
|
|
gptkbp:hasVariant
|
gptkb:VGG16
VGG19
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
VGGNet architecture
|
|
gptkbp:influenced
|
deep learning architectures
|
|
gptkbp:inputImageSize
|
224x224
|
|
gptkbp:inspiredBy
|
gptkb:ResNet
gptkb:AlexNet
other deep CNNs
|
|
gptkbp:introduced
|
gptkb:Andrew_Zisserman
gptkb:Karen_Simonyan
|
|
gptkbp:introducedIn
|
2014
|
|
gptkbp:level
|
16
19
|
|
gptkbp:notableAchievement
|
second place in ILSVRC 2014 classification
|
|
gptkbp:notableFor
|
use of small 3x3 convolution filters
very deep convolutional networks
simple and uniform architecture
|
|
gptkbp:notablePublication
|
gptkb:Very_Deep_Convolutional_Networks_for_Large-Scale_Image_Recognition
|
|
gptkbp:outputLayer
|
fully connected
|
|
gptkbp:usedFor
|
feature extraction
transfer learning
image classification
|
|
gptkbp:usedIn
|
gptkb:ImageNet_Large_Scale_Visual_Recognition_Challenge_2014
|
|
gptkbp:usesPooling
|
max pooling
|
|
gptkbp:bfsParent
|
gptkb:Very_Deep_Convolutional_Networks_for_Large-Scale_Image_Recognition
|
|
gptkbp:bfsLayer
|
7
|