2026-06-08T09:24:00Z https://b2share.fz-juelich.de/api/oai2d

oai:b2share.fz-juelich.de:b2rec/e19fe0f0bc0e4f1b8e05b28e977934c9 2020-07-15T19:44:55Z e9b9792e-79fb-4b07-b6b4-b9c2bd06d095

EUDAT https://b2share.fz-juelich.de/records/e19fe0f0bc0e4f1b8e05b28e977934c9 10.34730/e19fe0f0bc0e4f1b8e05b28e977934c9 EUDAT B2SHARE 2020 Elbert Jan Achterberg Evgenii Sovetkin Bart E. Pieters Thomas Weber # A training and testing dataset The dataset contains labelled images of thin-film modules collected during the PEARL project. This dataset is used in this paper: @article{sovetkin2020encoder, title={Encoder-decoder semantic segmentation models for electroluminescence images of thin-film modules}, author={Sovetkin, Evgenii and Weber, Thomas and Achterberg, Elbert Jan and Pieters, Bart Elger}, journal={IEEE Journal of Photovoltaics}, year={2020}, } ## Structure of the data The data is split onto 3 groups: training, testing and final_evaluation. Each group contains labelled images for droplets and shunts. All images are located in "images" directory. All labelled images are located in "labels" directory. Creative Commons Attribution-NonCommercial-NoDerivs (CC-BY-NC-ND) info:eu-repo/semantics/openAccess 5.6.23 → Engineering → Computer Science photovoltaics, encoder-decoder neural networks, thin-film, electroluminescence imaging gz b.pieters@fz-juelich.de 962.9 MB 1 file