LBMS-SAM: Segment anything model guided SEM image segmentation for lithium battery materials.
- DOI
- 10.1016/j.neunet.2025.108325
- Published
- 2026 Apr
- Container
- Neural networks : the official journal of the International Neural Network Society
- Publisher
- Not recorded
- Open access
- unknown
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limited evidence Score 43/100 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:10.1016/j.neunet.2025.108325,
title = {LBMS-SAM: Segment anything model guided SEM image segmentation for lithium battery materials.},
author = {Qi Y and Zhang J and Kuang J and Ren T and Wang D and Wu Z and Zheng H and Zhang Q},
year = {2026},
journal = {Neural networks : the official journal of the International Neural Network Society},
doi = {10.1016/j.neunet.2025.108325},
url = {https://doi.org/10.1016/j.neunet.2025.108325}
}RIS
TY - JOUR TI - LBMS-SAM: Segment anything model guided SEM image segmentation for lithium battery materials. AU - Qi Y AU - Zhang J AU - Kuang J AU - Ren T AU - Wang D AU - Wu Z AU - Zheng H AU - Zhang Q PY - 2026 JO - Neural networks : the official journal of the International Neural Network Society DO - 10.1016/j.neunet.2025.108325 UR - https://doi.org/10.1016/j.neunet.2025.108325 ER -
APA
Y, Q., J, Z., J, K., T, R., D, W., Z, W., H, Z., & Q, Z. (2026). LBMS-SAM: Segment anything model guided SEM image segmentation for lithium battery materials.. Neural networks : the official journal of the International Neural Network Society. https://doi.org/10.1016/j.neunet.2025.108325
Source records
- pubmed · retrieved 2026-09-26T19:17:59.302Z