Nuisance - OOPObjs

DOI

This dataset contains the database of Out Of Plane Objects (OOPObjs) extracted from PIV (Mie scattering) measurements within an RQL-type combustors. The database is one subclass utilised in the generation of synthetic training data via domain randomisation. The resulting dataset is subsequently used for training of DL-based image segmentation models. The resulting dataset is subsequently used for training of DL-based image segmentation models: B. Jose, K. P. Geigle, F. Hampp, Domain-Randomised Instance-Segmentation Benchmark for Soot in PIV Images, submitted to Machine Learning: Science and Technology (2025)

Identifier
DOI https://doi.org/10.18419/DARUS-5183
Metadata Access https://darus.uni-stuttgart.de/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.18419/DARUS-5183
Provenance
Creator Jose, Basil ORCID logo; Geigle, Klaus Peter ORCID logo; Hampp, Fabian ORCID logo
Publisher DaRUS
Contributor Jose, Basil; Hampp, Fabian
Publication Year 2025
Funding Reference DFG 456687251
Rights CC BY 4.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/licenses/by/4.0
OpenAccess true
Contact Jose, Basil (University of Stuttgart); Hampp, Fabian (University of Stuttgart)
Representation
Resource Type Dataset
Format image/png; application/zip; text/markdown
Size 2570; 3802; 3169; 3608211; 394
Version 1.0
Discipline Chemistry; Construction Engineering and Architecture; Engineering; Engineering Sciences; Fluid Mechanics; Heat Energy Technology, Thermal Machines, Fluid Mechanics; Mechanical and industrial Engineering; Mechanics; Mechanics and Constructive Mechanical Engineering; Natural Sciences; Thermal Engineering/Process Engineering