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#Org.neuroph.nnet.comp.layer Classes and Interfaces - 8 results found.
| Name | Description | Type | Package | Framework |
| CompetitiveLayer | Represents layer of competitive neurons, and provides methods for competition. | Class | org.neuroph.nnet.comp.layer | Neuroph |
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| ConvolutionalLayer | Convolutional layer is a special type of layer, used in convolutional neural networks. | Class | org.neuroph.nnet.comp.layer | Neuroph |
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| FeatureMapsLayer | This class represents an array of feature maps which are 2 dimensional layers (Layer2D instances) and it is base class for Convolution and Pooling layers, | Class | org.neuroph.nnet.comp.layer | Neuroph |
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| InputLayer | Represents a layer of input neurons - a typical neural network input layerAuthor:Zoran Sevarac See Also:InputNeuron, | Class | org.neuroph.nnet.comp.layer | Neuroph |
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| InputMapsLayer | Input layer for convolutional networksAuthor:Boris Fulurija, Zoran SevaracSee Also:Serialized Form | Class | org.neuroph.nnet.comp.layer | Neuroph |
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| Layer2D | 2D Layer provides 2D layout of the neurons in layer. | Class | org.neuroph.nnet.comp.layer | Neuroph |
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| Layer2D .Dimensions | Dimensions (width and height) of the Layer2DSee Also:Serialized Form | Class | org.neuroph.nnet.comp.layer | Neuroph |
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| PoolingLayer | Pooling layer is a special type of feature maps layer (FeatureMapsLayer) which is used in convolutional networks. | Class | org.neuroph.nnet.comp.layer | Neuroph |
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