Convpaint - Universal framework for interactive pixel classification using pretrained neural networks
Hinderling, L.; Witz, G.; Schwob, R.; Stojiljkovic, A.; Dobrzynski, M.; Vladymyrov, M.; Frei, J.; Graedel, B.; Frismantiene, A.; Pertz, O.
Show abstract
We develop Convpaint, a universal computational framework for interactive pixel classification. Convpaint utilizes pretrained convolutional neural networks (CNNs) or vision transformers (ViTs) for feature extraction and enables easy segmentation across a wide variety of tasks. Available within the Python-based napari software ecosystem, Convpaint integrates seamlessly with other plugins into image processing pipelines, which we demonstrate with three workflows across different data modalities.
Matching journals
The top 1 journal accounts for 50% of the predicted probability mass.