Wu et al. (2026) EWMT: Enhanced Wavelet Multi-head Transformer for Frequency-Decoupled Two-Input Spatiotemporal Fusion

Identification

• Journal: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
• Year: 2026
• Date: 2026-01-01
• Authors: Tongquan Wu, Weiquan Kong, Yuanxu Wang, Lu Bai, Yurong Qian
• DOI: 10.1109/jstars.2026.3676068

Research Groups

Not available from provided text.

Short Summary

This paper introduces EWMT, an Enhanced Wavelet Multi-head Transformer, designed for frequency-decoupled two-input spatiotemporal fusion.

Objective

• To develop and evaluate an Enhanced Wavelet Multi-head Transformer (EWMT) for effective frequency-decoupled two-input spatiotemporal fusion.

Study Configuration

• Spatial Scale: Not available from provided text (implied by "Spatiotemporal Fusion").
• Temporal Scale: Not available from provided text (implied by "Spatiotemporal Fusion").

Methodology and Data

• Models used: Enhanced Wavelet Multi-head Transformer (EWMT).
• Data sources: Two-input spatiotemporal data (specific sources not available from provided text).

Main Results

Not available from provided text.

Contributions

Not available from provided text.

Funding

Not available from provided text.

Citation

@article{Wu2026EWMT,
  author = {Wu, Tongquan and Kong, Weiquan and Wang, Yuanxu and Bai, Lu and Qian, Yurong},
  title = {EWMT: Enhanced Wavelet Multi-head Transformer for Frequency-Decoupled Two-Input Spatiotemporal Fusion},
  journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
  year = {2026},
  doi = {10.1109/jstars.2026.3676068},
  url = {https://doi.org/10.1109/jstars.2026.3676068}
}