Unmanned Aerial Systems and Deep Learning for Safety and Health Activity Monitoring on Construction Sites
- DOI
- 10.3390/s23156690
- Published
- 2023-07-26
- Container
- Sensors
- Publisher
- MDPI AG
- 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.
- 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.
- not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- 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:10.3390/s23156690,
title = {Unmanned Aerial Systems and Deep Learning for Safety and Health Activity Monitoring on Construction Sites},
author = {Aliu Akinsemoyin and Ibukun Awolusi and Debaditya Chakraborty and Ahmed Jalil Al-Bayati and Abiola Akanmu},
year = {2023},
journal = {Sensors},
doi = {10.3390/s23156690},
url = {https://doi.org/10.3390/s23156690}
}RIS
TY - JOUR TI - Unmanned Aerial Systems and Deep Learning for Safety and Health Activity Monitoring on Construction Sites AU - Aliu Akinsemoyin AU - Ibukun Awolusi AU - Debaditya Chakraborty AU - Ahmed Jalil Al-Bayati AU - Abiola Akanmu PY - 2023 JO - Sensors DO - 10.3390/s23156690 UR - https://doi.org/10.3390/s23156690 ER -
APA
Akinsemoyin, A., Awolusi, I., Chakraborty, D., Al-Bayati, A. J., & Akanmu, A. (2023). Unmanned Aerial Systems and Deep Learning for Safety and Health Activity Monitoring on Construction Sites. Sensors. https://doi.org/10.3390/s23156690
Source records
- crossref · retrieved 2026-09-25T16:30:46.460Z