A Forward and Backward Compatible Framework for Few-Shot Class-Incremental Pill Recognition

Jinghua Zhang, Li Liu, Kai Gao, Dewen Hu

Open source

DOI: 10.1109/tnnls.2024.3497956
Published: 2025-06
Container: IEEE Transactions on Neural Networks and Learning Systems
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Open access: unknown

Credibility signals

uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

supportingDOI registered: A matching record was returned by Crossref. Source: Crossref; license: CC0 metadata
supportingDOI resolves: A matching record was returned by Crossref. Source: Crossref; license: CC0 metadata
not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. 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
not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
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
supportingMetadata completeness: All 6 scored descriptive metadata groups are present. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer

Cite this work

BibTeX

@article{allodium:10.1109/tnnls.2024.3497956,
  title = {A Forward and Backward Compatible Framework for Few-Shot Class-Incremental Pill Recognition},
  author = {Jinghua Zhang and Li Liu and Kai Gao and Dewen Hu},
  year = {2025},
  journal = {IEEE Transactions on Neural Networks and Learning Systems},
  doi = {10.1109/tnnls.2024.3497956},
  url = {https://doi.org/10.1109/tnnls.2024.3497956}
}

RIS

TY  - JOUR
TI  - A Forward and Backward Compatible Framework for Few-Shot Class-Incremental Pill Recognition
AU  - Jinghua Zhang
AU  - Li Liu
AU  - Kai Gao
AU  - Dewen Hu
PY  - 2025
JO  - IEEE Transactions on Neural Networks and Learning Systems
DO  - 10.1109/tnnls.2024.3497956
UR  - https://doi.org/10.1109/tnnls.2024.3497956
ER  -

APA

Zhang, J., Liu, L., Gao, K., & Hu, D. (2025). A Forward and Backward Compatible Framework for Few-Shot Class-Incremental Pill Recognition. IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/tnnls.2024.3497956

Source records

crossref · retrieved 2026-09-25T17:20:59.613Z