DeprecatedKNIME Deep Learning - Keras Integration version 3.7.2.v201904170930 by KNIME AG, Zurich, Switzerland
The need for transposed convolutions generally arises from the desire to use a transformation going in the opposite direction of a normal convolution, i.e., from something that has the shape of the output of some convolution to something that has the shape of its input while maintaining a connectivity pattern that is compatible with said convolution. Corresponds to the Keras Transposed Convolution 2D Layer.
To use this node in KNIME, install KNIME Deep Learning - Keras Integration from the following update site:
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