Hybrid Optimized GRU-ECNN Models for Gait Recognition with Wearable IOT Devices
- DOI
- 10.1155/2022/5422428
- Published
- 2022-05-13
- Container
- Computational Intelligence and Neuroscience
- Publisher
- Wiley
- Open access
- unknown
Credibility signals
serious concern Score 29/100 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.
- supportingDOI resolves: A matching record was returned by Crossref.
- 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.
- not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made.
- not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made.
- not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made.
- not scoredROR affiliation: Not checked or no result supplied; no credibility inference made.
- serious concernRetraction Watch retraction: 1 retraction notice matched this DOI.
- 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.
- not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredOpen access status: Not checked or no result supplied; no credibility inference made.
- not scoredPublication license: Not checked or no result supplied; no credibility inference made.
- not scoredPublication version: A publication version was supplied but is not scored.
- supportingMetadata completeness: All 6 scored descriptive metadata groups are present.
Cite this work
BibTeX
@article{allodium:10.1155/2022/5422428,
title = {Hybrid Optimized GRU-ECNN Models for Gait Recognition with Wearable IOT Devices},
author = {K. M. Monica and R. Parvathi and A. Gayathri and Rajanikanth Aluvalu and K. Sangeetha and Chennareddy Vijay Simha Reddy},
year = {2022},
journal = {Computational Intelligence and Neuroscience},
doi = {10.1155/2022/5422428},
url = {https://doi.org/10.1155/2022/5422428}
}RIS
TY - JOUR TI - Hybrid Optimized GRU-ECNN Models for Gait Recognition with Wearable IOT Devices AU - K. M. Monica AU - R. Parvathi AU - A. Gayathri AU - Rajanikanth Aluvalu AU - K. Sangeetha AU - Chennareddy Vijay Simha Reddy PY - 2022 JO - Computational Intelligence and Neuroscience DO - 10.1155/2022/5422428 UR - https://doi.org/10.1155/2022/5422428 ER -
APA
Monica, K. M., Parvathi, R., Gayathri, A., Aluvalu, R., Sangeetha, K., & Reddy, C. V. S. (2022). Hybrid Optimized GRU-ECNN Models for Gait Recognition with Wearable IOT Devices. Computational Intelligence and Neuroscience. https://doi.org/10.1155/2022/5422428
Source records
- crossref · retrieved 2026-09-25T04:17:51.844Z