Assertion: deep neural network | /r/HasProperty | dnn
Facets:
Source sentences:
text: A deep neural network (DNN) is an artificial neural network (ANN) with multiple layers between the input and output layers.
text: Artificial neural networks with multiple hidden layers between the input and output layers are called deep neural networks (DNNs), and they can model complex nonlinear relationships.
text: A DBN can be used to generatively pre-train a deep neural network (DNN) by using the learned DBN weights as the initial DNN weights.
text: A deep neural network (DNN) is an ANN with multiple hidden layers between the input and output layers.
text: A Deep Neural Network (DNN) has two or more “hidden layers” of neurons that process inputs.
text: Convolutional Neural Network (CNN) is a class of deep neural network (DNN) which is widely used for computer vision or NLP.
text: A deep neural network (DNN) is an ANN with multiple hidden layers of units between the input and output layers which can be discriminatively trained with the standard backpropagation algorithm.
text: However, recent research has shown that deep neural networks (DNN) with many layers can be very effective in complex tasks such as image or speech recognition.
text: However, recent research has shown that deep neural networks (DNN) with many layers can be very effective in complex tasks such as image or speech recognition.