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shape: 150, 150, 1filters: 32kernel size: 3x3activation: ReLUpool size: 2x2units: 64kernel size: 3x3activation: ReLUpool size: 2x2units: 64activation: ReLUdropout: 0.5units: 1activation: sigmoidTrain the model for 10 epochs (Adam) withloss function binary crossentropyApply the modelon new dataoutput >= 0.5 Happyoutput < 0.5 SadEvaluate the modelaccuracyResize to 150x150Path to training imagesNormalize between 0..1Read imagesRemove superfluous columnsSave modelSet up condaenvironmentEncode classeswith 0 and 1units: 64kernel size: 3x3activation: ReLUpool size: 2x2Keras Input Layer Keras Convolution2D Layer Keras Max Pooling2D Layer Keras Convolution2D Layer Keras Max Pooling2D Layer Keras Flatten Layer Keras Dense Layer Keras Dropout Layer Keras Dense Layer Keras NetworkLearner Keras NetworkExecutor Rule Engine Scorer Image Resizer Paths to images Image Calculator Image Reader(Table) Column Filter Partitioning Keras NetworkWriter Conda EnvironmentPropagation Rule Engine Visualize results Keras Convolution2D Layer Keras Max Pooling2D Layer shape: 150, 150, 1filters: 32kernel size: 3x3activation: ReLUpool size: 2x2units: 64kernel size: 3x3activation: ReLUpool size: 2x2units: 64activation: ReLUdropout: 0.5units: 1activation: sigmoidTrain the model for 10 epochs (Adam) withloss function binary crossentropyApply the modelon new dataoutput >= 0.5 Happyoutput < 0.5 SadEvaluate the modelaccuracyResize to 150x150Path to training imagesNormalize between 0..1Read imagesRemove superfluous columnsSave modelSet up condaenvironmentEncode classeswith 0 and 1units: 64kernel size: 3x3activation: ReLUpool size: 2x2Keras Input Layer Keras Convolution2D Layer Keras Max Pooling2D Layer Keras Convolution2D Layer Keras Max Pooling2D Layer Keras Flatten Layer Keras Dense Layer Keras Dropout Layer Keras Dense Layer Keras NetworkLearner Keras NetworkExecutor Rule Engine Scorer Image Resizer Paths to images Image Calculator Image Reader(Table) Column Filter Partitioning Keras NetworkWriter Conda EnvironmentPropagation Rule Engine Visualize results Keras Convolution2D Layer Keras Max Pooling2D Layer

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Created by: prath
Created at: 2023-02-23
On NodePit since: 2023-02-26
Last update: 2024-11-21
Created with KNIME version: v4.7.1

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