Datasets from "MaskTerial: A Foundation Model for Automated 2D Material Flake Detection"

JuSER (Forschungszentrum Jülich)

Abstract

The detection and classification of exfoliated two-dimensional (2D) material flakes from optical microscope images can be automated using computer vision algorithms. This has the potential to increase the accuracy and objectivity of classification and the efficiency of sample fabrication, and it allows for large-scale data collection. Existing algorithms often exhibit challenges in identifying low-contrast materials and typically require large amounts of training data. Here, we present a deep learning model, called MaskTerial, that uses an instance segmentation network to reliably identify 2D material flakes. The model is extensively pre-trained using a synthetic data generator, that generates realistic microscopy images from unlabeled data. This results in a model that can to quickly adapt to new materials with as little as 5 to 10 images. Furthermore, an uncertainty estimation model is used to finally classify the predictions based on optical contrast. We evaluate our method on eight different datasets comprising five different 2D materials and demonstrate significant improvements over existing techniques in the detection of low-contrast materials such as hexagonal boron nitride.

Authors 6

1. Jan-Lucas Uslu Aachen 2nd Institute of Physics and JARA-FIT Visual Computing Institute

   RWTH Aachen University

   Affiliation as printed

   2nd Institute of Physics and JARA-FIT , RWTH Aachen University , 52074 Aachen , Germany

   Visual Computing Institute , RWTH Aachen University , 52074 Aachen , Germany

2. Alexander Hermans Aachen Visual Computing Institute

   RWTH Aachen University

   Affiliation as printed

   Visual Computing Institute , RWTH Aachen University , 52074 Aachen , Germany

3. Bernd Beschoten Aachen 2nd Institute of Physics and JARA-FIT

   RWTH Aachen University

   Affiliation as printed

   2nd Institute of Physics and JARA-FIT , RWTH Aachen University , 52074 Aachen , Germany

4. Bastian Leibe Aachen Visual Computing Institute

   RWTH Aachen University

   Affiliation as printed

   Visual Computing Institute , RWTH Aachen University , 52074 Aachen , Germany

5. Lutz Waldecker Aachen 2nd Institute of Physics and JARA-FIT

   RWTH Aachen University

   Affiliation as printed

   2nd Institute of Physics and JARA-FIT , RWTH Aachen University , 52074 Aachen , Germany

6. Christoph Stampfer Aachen 2nd Institute of Physics and JARA-FIT

   Forschungszentrum Jülich · Ernst Ruska Centre · RWTH Aachen University

   Affiliation as printed

   2nd Institute of Physics and JARA-FIT , RWTH Aachen University , 52074 Aachen , Germany

   Peter Grünberg Institute (PGI-9 ) Forschungszentrum Jülich , 52425 Jülich , Germany