|
gptkbp:instanceOf
|
gptkb:convolutional_neural_network
|
|
gptkbp:accuracyTop1
|
68.7%
|
|
gptkbp:accuracyTop5
|
93.3%
|
|
gptkbp:alsoKnownAs
|
gptkb:GoogLeNet
|
|
gptkbp:architecture
|
deep convolutional neural network
|
|
gptkbp:arXivID
|
1409.4842
|
|
gptkbp:author
|
gptkb:Scott_Reed
gptkb:Vincent_Vanhoucke
gptkb:Wei_Liu
gptkb:Christian_Szegedy
gptkb:Dragomir_Anguelov
gptkb:Dumitru_Erhan
gptkb:Pierre_Sermanet
gptkb:Yangqing_Jia
gptkb:Andrew_Rabinovich
|
|
gptkbp:developedBy
|
gptkb:Google
|
|
gptkbp:frameworksAvailableIn
|
gptkb:TensorFlow
gptkb:Caffe
gptkb:PyTorch
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
Inception-v1
|
|
gptkbp:inputImageSize
|
224x224
|
|
gptkbp:inspiredBy
|
gptkb:Network-in-Network_architecture
|
|
gptkbp:introducedIn
|
gptkb:CVPR_2015
2014
|
|
gptkbp:level
|
22
|
|
gptkbp:notableFeature
|
1x1 convolutions
inception module
parallel convolutional filters
|
|
gptkbp:notableFor
|
computational efficiency
reduced number of parameters
|
|
gptkbp:notablePublication
|
gptkb:Going_Deeper_with_Convolutions
|
|
gptkbp:predecessor
|
gptkb:AlexNet
|
|
gptkbp:publishedIn
|
gptkb:CVPR_2015
|
|
gptkbp:successor
|
gptkb:Inception-v2
gptkb:Inception-v3
gptkb:Inception-v4
|
|
gptkbp:trainer
|
gptkb:ImageNet
|
|
gptkbp:usedFor
|
image classification
object detection
|
|
gptkbp:won
|
gptkb:ILSVRC_2014
|
|
gptkbp:bfsParent
|
gptkb:Inception_module
|
|
gptkbp:bfsLayer
|
7
|