Train a deep-learning model for image-classification into 2 target categories.
The training is done by transfer learning of a VGG-16 base pretrained on the ImageNet dataset, completed by freshly initialized fully connected classification layers.
Category ground-truth annotations should be done in Fiji using the Qualitative-Annotation plugins, see reference below.
If you use this workflow please cite :
Thomas LSV, Schaefer F and Gehrig J.
Fiji plugins for qualitative image annotations: routine analysis and application to image classification
[version 1; peer review: awaiting peer review].
F1000Research 2020, 9:1248
doi: 10.12688/f1000research.26872.1
Workflow
Train VGG16 for binary image-classification
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Created with KNIME Analytics Platform version 4.2.3
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