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November 30, 2025˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciencesOpen Access

Enhanced Change Detection Method in Historical Districts: A Lightweight Visual Transformer Integration Model with Context-Aware Local Feature Augmentation

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Authors

LHLujin HuSDSenchuan DiBeijing University of Civil Engineering and ArchitectureLHLujin Hu

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Overview

The analysis shows improved performance metrics for change detection in urban environments, highlighting a solution for historic district preservation.

Key Points

  • Significant improvements in performance metrics were observed in the context of change detection.
  • The model enhances change detection by effectively addressing urbanization challenges in dense areas.
  • Analysis of the public LEVIR-CD dataset demonstrated the model's robust capabilities.
  • This work supports efforts for preserving historic districts by reducing detection omissions and false positives.

Cite This Study

Hu et al. (2025) studied this question.

synapsesocial.com/papers/692b94581d383f2b2a378e8fhttps://doi.org/10.5194/isprs-archives-xlviii-4-w14-2025-69-2025
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Also Consider

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

  1. 1Enhanced Change Detection Method in Historical Districts: A Lightweight Visual Transformer Integration Model with Context-Aware Local Feature Augmentation2025
  2. 2A Transformer-Based Multi-Scale Semantic Extraction Change Detection Network for Building Change Application2025
  3. 3VLM-Based Building Change Detection with CNN-Transformer2025
  4. 4A CNN- and Transformer-Based Dual-Branch Network for Change Detection with Cross-Layer Feature Fusion and Edge Constraints2024 · 10 citations
  5. 5Siamese Transformer-Based Building Change Detection in Remote Sensing Images2024 · 13 citations