MAPUNet Model Parameters and Inference Time for Mining Area Deformation

Model parameters and inference time data for MAPUNet, a multi-scale phase unwrapping method designed for monitoring large gradient deformations in mining areas. The dataset was published by Baojing Zhang on figshare under a CC-BY-4.0 license and last updated on May 26, 2026. It likely contains performance metrics and parameters for the proposed neural network model.

Use Cases

• Benchmarking phase unwrapping model performance based on simulated interferograms with different signal-to-noise ratios.
• Analyzing model robustness and accuracy improvements based on reported SSIM metrics.
• Applying deformation inversion models to real mining area interferograms based on the described methodology.

Strengths

• The dataset is associated with a specific, novel method (MAPUNet) described in a research paper.
• Performance metrics are reported, including SSIM increases of 0.0176 and 0.298 compared to other models.
• The dataset has a clear license (CC-BY-4.0) and author attribution.

Limitations

• The dataset is very small (5.5 KB), suggesting limited scope.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

figshare

Collection Method

Likely generated from experiments with simulated interferograms and a real mining area case study.

Freshness

Last updated 2026-05-26 17:39:14; freshness should be verified.

Geography

A mining area in Shanxi, China, is referenced in the description.