Analyzing mixed construction and demolition waste in material recovery facilities: Evolution, challenges, and applications of computer vision and deep learning
- DOI
- 10.1016/j.resconrec.2025.108218
- Published
- 2025-05
- Container
- Resources, Conservation and Recycling
- Publisher
- Elsevier BV
- 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:10.1016/j.resconrec.2025.108218,
title = {Analyzing mixed construction and demolition waste in material recovery facilities: Evolution, challenges, and applications of computer vision and deep learning},
author = {Adrian Langley and Matthew Lonergan and Tao Huang and Mostafa Rahimi Azghadi},
year = {2025},
journal = {Resources, Conservation and Recycling},
doi = {10.1016/j.resconrec.2025.108218},
url = {https://doi.org/10.1016/j.resconrec.2025.108218}
}RIS
TY - JOUR TI - Analyzing mixed construction and demolition waste in material recovery facilities: Evolution, challenges, and applications of computer vision and deep learning AU - Adrian Langley AU - Matthew Lonergan AU - Tao Huang AU - Mostafa Rahimi Azghadi PY - 2025 JO - Resources, Conservation and Recycling DO - 10.1016/j.resconrec.2025.108218 UR - https://doi.org/10.1016/j.resconrec.2025.108218 ER -
APA
Langley, A., Lonergan, M., Huang, T., & Azghadi, M. R. (2025). Analyzing mixed construction and demolition waste in material recovery facilities: Evolution, challenges, and applications of computer vision and deep learning. Resources, Conservation and Recycling. https://doi.org/10.1016/j.resconrec.2025.108218
Source records
- crossref · retrieved 2026-09-27T03:13:34.658Z