Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
October 11, 2025Information Technology And ControlOpen Access

The Application of Transformer Model in Building Information Modeling

View Full Paper
Ask AI
Bookmark
Share

Authors

ZWZhe Wang

Discussion

Loading...

Member takes

Overview

This research demonstrates improved change detection in urban settings using a transformer model and satellite imagery.

Key Points

  • The model achieves 95% accuracy in change detection tasks, indicating significant effectiveness in urban monitoring.
  • Key improvements include a 1.37% increase in mean Intersection over Union (mIoU) and a high Kappa value of 0.795.
  • The integration of convolutional neural networks with transformers allows for better local feature extraction and global context modeling.
  • Lightweight design innovations reduce computational costs, making the model suitable for real-time applications.

Cite This Study

Zhe Wang (2025) studied this question.

synapsesocial.com/papers/68e9b2e4ba7d64b6fc1330d8https://doi.org/10.5755/j01.itc.54.3.41147
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1VLM-Based Building Change Detection with CNN-Transformer2025
  2. 2Siamese Transformer-Based Building Change Detection in Remote Sensing Images2024 · 12 citations
  3. 3Building extraction method in complex scenes of remote sensing based on transformer2024
  4. 4Cross-level and multiscale CNN-Transformer network for automatic building extraction from remote sensing imagery2024 · 11 citations
  5. 5STransU2Net: Transformer based hybrid model for building segmentation in detailed satellite imagery2024 · 4 citations