Run FORC inversion from experimental data
FORCINN applies a convolutional neural network trained on synthetic FORC diagrams to invert experimental measurements into grain size and aspect ratio distributions. Upload a FORC file from an AGM or VSM instrument, choose the appropriate mode, and the pipeline handles noise estimation, slope correction (optional), and inversion automatically.
For context on how the CNN model was trained and validated against experimental measurements, see the Publications page. For the underlying micromagnetic framework, refer to the About page or the user manual.