Deep spectral feature fusion network combined with attention mechanism to predict heavy metal elements in soil by XRF
Prediction of heavy metal elements in soil using XRF based on the deep feature fusion model (Spec-SAFFNet) that integrates a feature fusion module (FFM) with a self-attention-enhanced one-dimensional convolutional neural network (SA-1DCNN).
Authors
- Shubin Lyu (ORCID: https://orcid.org/0000-0002-4454-4646)
- Fusheng Li (ORCID: https://orcid.org/0000-0003-3455-0855)
- Yichen Guo (ORCID: https://orcid.org/0000-0002-7487-3205)
- Xiaohe Qu
- Siyu Chen
Institutions
- University of Electronic Science and Technology of China (CN)
- Huzhou Normal University (CN)
Publication Details
- Journal
- Journal of Analytical Atomic Spectrometry
- Published
- 2025-12-26
- DOI
- https://doi.org/10.1039/d5ja00369e
- Primary Topic
- Soil Geostatistics and Mapping
- Type
- article
- Field-Weighted Citation Impact
- 0.00