|
gptkbp:instance_of
|
gptkb:neural_networks
|
|
gptkbp:architecture
|
gptkb:Deep_Learning
|
|
gptkbp:coat_of_arms
|
gptkb:19
|
|
gptkbp:dataset_trained_on
|
gptkb:Image_Net
|
|
gptkbp:developed_by
|
gptkb:Visual_Geometry_Group
|
|
gptkbp:dropout
|
gptkb:Yes
|
|
gptkbp:feature_extractor
|
gptkb:Yes
|
|
gptkbp:has_publications
|
Very Deep Convolutional Networks for Large-Scale Image Recognition
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
VGG19
|
|
gptkbp:image_input
|
RGB Images
|
|
gptkbp:image_net_rank
|
Top-5 accuracy 92.7%
|
|
gptkbp:initiated_by
|
Re LU
|
|
gptkbp:input_output
|
224x224
|
|
gptkbp:is_a_framework_for
|
gptkb:Tensor_Flow
gptkb:Py_Torch
|
|
gptkbp:is_optimized_for
|
Stochastic Gradient Descent
|
|
gptkbp:is_standardized_by
|
No
|
|
gptkbp:layer_type
|
gptkb:swimming_pool
Convolutional Layer
Fully Connected Layer
|
|
gptkbp:losses
|
Cross-Entropy Loss
|
|
gptkbp:max_pooling
|
gptkb:Yes
|
|
gptkbp:migration
|
gptkb:Yes
|
|
gptkbp:notable_for
|
High accuracy in image classification tasks
|
|
gptkbp:orbital_period
|
143.67 million
|
|
gptkbp:output_activation
|
Softmax
|
|
gptkbp:predecessor
|
gptkb:VGG16
|
|
gptkbp:resolution
|
1000
|
|
gptkbp:successor
|
gptkb:VGG16_with_Batch_Normalization
|
|
gptkbp:training
|
Long
|
|
gptkbp:used_for
|
Image Classification
|
|
gptkbp:year_created
|
gptkb:2014
|
|
gptkbp:bfsParent
|
gptkb:VGGNet
|
|
gptkbp:bfsLayer
|
5
|