CCD-based melt pool annotation inLW-DED

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Authors: Reza Asadi
Cited by: 1

Abstract

Melt pool images with related annotations in LW-DED processes with Stainless Steel (SS) and low carbon steel (S355) substrates and Inconel 625 wire material are provided for instance segmentation methods. The annotation of all images in the dataset was carried out utilizing the "labelme" library, which is a Python package. This library offers an image annotation tool and various functionalities for reading, writing, and converting the resulting annotations in JSON format. As the complementary data, 3D scanned data as well as microscopy images of the cross-sections of the deposited beads on the mentioned substrates and wire feedstock are provided in the dataset.

Fields of Study & Subjects

Industrial Vision Systems and Defect Detection Advanced Algorithms and Applications

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
22 June 2026
Language
EN
Document type
Dataset