The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/21387930

Richie Maskam; Amiri-Simkooei, A. (Alireza); Sander van Nederveen; Mohammad Fotouhi; Maarten Visser (2022): Data underlying the student thesis: Automated monitoring of corrosion on piling sheets. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/21387930.v1

Dataset

• Civil Engineering
• Other Construction

Computer Vision, deep learning dataset, Life cycle asset management, Piling sheet, YOLOv4

CC BY 4.0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Richie Maskam, A. (Alireza) Amiri-Simkooei , Sander van Nederveen, Mohammad Fotouhi, Maarten Visser

 This is a piling sheet data used for classification and object detection. The classes are based on Digiggids. Object detection was used to detect dimensional features and estimate dimensions that could tell us about the type of piling sheet. 

 For the notebooks you can check my github page. 

• 2022-10-25 first online, published, posted

4TU.ResearchData

*.jpg; *.txt

• http://resolver.tudelft.nl/uuid%3Aefcf9290-efc4-4b94-8881-c75484873c21
• https://github.com/Harsono-stack/Piling-sheet-assesment-

TU Delft, Faculty of Civil Engineering and Geosciences
Witteveen+Bos N.V.