An in-depth analysis of data reduction methods for sustainable deep learning.

Perera-Lago J, Toscano-Duran V, Paluzo-Hidalgo E, Gonzalez-Diaz R, Gutiérrez-Naranjo MA, Rucco M

Open source

DOI: 10.12688/openreseurope.17554.2
Published: 2024
Container: Open research Europe
Publisher: Not recorded
Open access: yes

Credibility signals

uncertain Score 53/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
cautionDOI resolves: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
supportingDirectory of Open Access Journals: A matching record was returned by DOAJ. Source: DOAJ; license: CC0
not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
supportingOpen access status: Normalized open-access status: open. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer

Cite this work

BibTeX

@article{allodium:10.12688/openreseurope.17554.2,
  title = {An in-depth analysis of data reduction methods for sustainable deep learning.},
  author = {Perera-Lago J and Toscano-Duran V and Paluzo-Hidalgo E and Gonzalez-Diaz R and Gutiérrez-Naranjo MA and Rucco M},
  year = {2024},
  journal = {Open research Europe},
  doi = {10.12688/openreseurope.17554.2},
  url = {https://doi.org/10.12688/openreseurope.17554.2}
}

RIS

TY  - JOUR
TI  - An in-depth analysis of data reduction methods for sustainable deep learning.
AU  - Perera-Lago J
AU  - Toscano-Duran V
AU  - Paluzo-Hidalgo E
AU  - Gonzalez-Diaz R
AU  - Gutiérrez-Naranjo MA
AU  - Rucco M
PY  - 2024
JO  - Open research Europe
DO  - 10.12688/openreseurope.17554.2
UR  - https://doi.org/10.12688/openreseurope.17554.2
ER  -

APA

J, P., V, T., E, P., R, G., MA, G., & M, R. (2024). An in-depth analysis of data reduction methods for sustainable deep learning.. Open research Europe. https://doi.org/10.12688/openreseurope.17554.2

Source records

pubmed · retrieved 2026-09-25T21:56:35.130Z
europe-pmc · retrieved 2026-09-25T21:56:35.134Z
europe-pmc · retrieved 2026-09-25T21:56:35.134Z
doaj · retrieved 2026-09-25T21:56:35.139Z