NFFA online Scanning Electron Microscopy classifier automatically classify and tag your nano-images.

Some information coming from the instrument (Beamtime, Gun Vacuum, EHT, and so on) are automatically built into the images, but information about the target material is missing. Tagging the content of SEM images in a uniform way aims to produce Findable, Accessible, Interoperable and Retrievable data. 
Different neural network architectures were trained and tested on a dataset of human-labelled SEM images. The best model achieved was used as the engine of the online analysis service we developed to automatically classify newly incoming images.
If you are not satisfied with the result, you can manually insert a new category.

Upload your SEM images and help us improving the performance of our neural network.

The map of techniques

at MM building at Q2 building at Elettra experimental hall at CNR-IOM cloud at Fermi-T-Rex laboratory Surface & Nano Science Lab, STM/STS PLD XPS & ambient pressure XAS ARPES & Spin ARPES MOKE & Masked deposition system XPS MBE Oxides SPRINT laboratory SEM XRD PVD data repository open data data analysis
add to wishlist

Scientists in charge