U-Net 2D - Encoding Layer

This component can be used for the encoding layers of a U-Net for 2D data. The following layers are used:

* 2D Convolution Layer
* Dropout Layer
* 2D Convolution Layer
* Max Pooling 2D Layer

An input is required for:
* Filter size for the Convolution layers, e.g. 16
* Activation Function for the Convolution layers, e.g. ELU
* Kernel Size for the Convolution layers, e.g. 3,3
* Dropout Rate for the Dropout layer, e.g. 0.1
* Random seed for the Dropout layer and for the Kernel Initializer in Convolution layers, e.g. 12345
* Pool Size (and Strides) for the Max Pooling layer, e.g. 2,2


The following settings are fixed and passed to the U-Net 2D - Decoding Layer component:
* Strides for the Convolution layers are set to 1,1
* Padding for the Convolution layers is set to "SAME"
* Kernel Initializer for the Convolution layers is set to "He Normal"

The corresponding U-Net 2D - Decoding Layer component can be used to create a complete U-Net.

The required extensions:
- KNIME Deep Learning - Keras Integration

Options

Dropout Rate

Fraction of the input units to drop.

2D Convolution Filter

The dimensionality of the output space (i.e. the number of output filters in the convolution).

Random Seed

Random seed for Dropout Layer

Activation Function

The activation function to use.

Kernel Size

A tuple of 2 integers, specifying the height and width of the 2D convolution window.

MaxPooling Pool Size

The size of the pooling window in two dimensions.%%00010

Nodes

• Breakpoint4 ×
• String Manipulation (Variable)3 ×
• Table Row to Variable3 ×
• Cell Splitter2 ×
• Column Filter2 ×
• Show all 19 nodes

Extensions

• FeatureKNIME Base nodes
• FeatureKNIME Deep Learning - Keras Integration
• FeatureKNIME Javasnippet
• FeatureKNIME Quick Forms

Links

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