Energy consumption forecasting for laser manufacturing of large artifacts based on fusionable transfer learning.
- DOI
- 10.1186/s42492-024-00178-3
- Published
- 2024 Dec 2
- Container
- Visual computing for industry, biomedicine, and art
- Publisher
- Not recorded
- Open access
- yes
Credibility signals
limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.1186/s42492-024-00178-3,
title = {Energy consumption forecasting for laser manufacturing of large artifacts based on fusionable transfer learning.},
author = {Wang L and Xu J and Zhang S and Tan J and Fei S and Shi X and Pang J and Luo S},
year = {2024},
journal = {Visual computing for industry, biomedicine, and art},
doi = {10.1186/s42492-024-00178-3},
url = {https://doi.org/10.1186/s42492-024-00178-3}
}RIS
TY - JOUR TI - Energy consumption forecasting for laser manufacturing of large artifacts based on fusionable transfer learning. AU - Wang L AU - Xu J AU - Zhang S AU - Tan J AU - Fei S AU - Shi X AU - Pang J AU - Luo S PY - 2024 JO - Visual computing for industry, biomedicine, and art DO - 10.1186/s42492-024-00178-3 UR - https://doi.org/10.1186/s42492-024-00178-3 ER -
APA
L, W., J, X., S, Z., J, T., S, F., X, S., J, P., & S, L. (2024). Energy consumption forecasting for laser manufacturing of large artifacts based on fusionable transfer learning.. Visual computing for industry, biomedicine, and art. https://doi.org/10.1186/s42492-024-00178-3
Source records
- pubmed · retrieved 2026-09-25T08:42:23.207Z