This is a radiographic image dataset for weld defects classification. The RIAWELC dataset collects 24,407 224x224 8-bit radiographic images digitalized in the .png format Four classes of weld defects are represented: lack of penetration (LP), porosity (PO), cracks (CR) and no defect (ND)
The dataset is released freely. If you use RIAWELC, please cite the following papers:
[1] Benito Totino, Fanny Spagnolo, Stefania Perri, "RIAWELC: A Novel Dataset of Radiographic Images for Automatic Weld Defects Classification", in the Proceedings of the Interdisciplinary Conference on Mechanics, Computers and Electrics (ICMECE 2022), 6-7 October 2022, Barcelona, Spain.
[2] Stefania Perri, Fanny Spagnolo, Fabio Frustaci, Pasquale Corsonello, "Welding Defects Classification Through a Convolutional Neural Network", in press in Manufacturing Letters, Elsevier.