Toward GAN-Based Multimodal Novelty etection for Industrial Fault Taxonomy Expansion: A Feasibility Study

Dinesh Surisetti

DOI: 10.5281/zenodo.22934091
Published: 2026
Container: Not recorded
Publisher: IJERT.ORG
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.5281/zenodo.22934091,
  title = {Toward GAN-Based Multimodal Novelty etection for Industrial Fault Taxonomy Expansion: A Feasibility Study},
  author = {Dinesh Surisetti},
  year = {2026},
  doi = {10.5281/zenodo.22934091},
  url = {https://doi.org/10.5281/zenodo.22934091}
}

RIS

TY  - JOUR
TI  - Toward GAN-Based Multimodal Novelty etection for Industrial Fault Taxonomy Expansion: A Feasibility Study
AU  - Dinesh Surisetti
PY  - 2026
DO  - 10.5281/zenodo.22934091
UR  - https://doi.org/10.5281/zenodo.22934091
ER  -

APA

Surisetti, D. (2026). Toward GAN-Based Multimodal Novelty etection for Industrial Fault Taxonomy Expansion: A Feasibility Study. https://doi.org/10.5281/zenodo.22934091

Source records

datacite · retrieved 2026-09-25T01:20:28.655Z