|
gptkbp:instanceOf
|
gptkb:convolutional_neural_network
|
|
gptkbp:abbreviation
|
gptkb:convolutional_neural_network
|
|
gptkbp:consistsOf
|
layers
neurons
|
|
gptkbp:developedBy
|
1940s
|
|
gptkbp:hasApplication
|
gptkb:dictionary
control systems
robotics
diagnosis
function approximation
game playing
regression
clustering
forecasting
financial prediction
|
|
gptkbp:hasComponent
|
hidden layer
input layer
output layer
|
|
gptkbp:hasType
|
gptkb:convolutional_neural_network
gptkb:feedforward_neural_network
gptkb:radial_basis_function_network
recurrent neural network
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
ANN
|
|
gptkbp:inspiredBy
|
biological neural networks
|
|
gptkbp:limitation
|
computationally intensive
require large datasets
overfitting
vanishing gradient problem
|
|
gptkbp:notableContributor
|
gptkb:Geoffrey_Hinton
gptkb:Walter_Pitts
gptkb:Warren_McCulloch
gptkb:Yann_LeCun
gptkb:Yoshua_Bengio
gptkb:Frank_Rosenblatt
gptkb:Jürgen_Schmidhuber
|
|
gptkbp:relatedTo
|
gptkb:artificial_intelligence
gptkb:machine_learning
gptkb:model
gptkb:perceptron
|
|
gptkbp:trainer
|
backpropagation
gradient descent
|
|
gptkbp:usedIn
|
gptkb:machine_learning
deep learning
natural language processing
speech recognition
image processing
pattern recognition
|
|
gptkbp:bfsParent
|
gptkb:All-Nippon_News_Network_(ANN)
gptkb:Adventist_News_Network
|
|
gptkbp:bfsLayer
|
6
|