Dual-stream hybrid architecture with adaptive multi-scale boundary-aware mechanisms for robust urban change detection in smart cities
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View abstract on PubMed
Summary
This summary is machine-generated.This study introduces a Dual-Stream Hybrid Architecture (DSHA) for improved urban change detection in remote sensing. The novel method enhances monitoring of land cover and infrastructure changes for smart city development.
Area Of Science
- Remote Sensing
- Computer Vision
- Urban Planning
Background
- Urban environments experience continuous changes requiring effective monitoring for sustainable development.
- Deep learning methods for remote sensing change detection often struggle with complex scenarios like multi-scale features and imprecise boundaries.
- Existing per-pixel labeling approaches face limitations in accurately detecting subtle changes and handling domain shifts.
Purpose Of The Study
- To propose a novel Dual-Stream Hybrid Architecture (DSHA) for robust and accurate urban change detection.
- To address limitations of current deep learning methods in handling complex urban environmental changes.
- To enhance smart city monitoring applications through improved land cover and infrastructure change detection.
Main Methods
- Developed a Dual-Stream Hybrid Architecture (DSHA) integrating ResNet34 and Modified Pyramid Vision Transformer (PVT-v2).
- Incorporated a boundary-aware module and multiscale attention in the decoder for precise object boundary detection.
- Utilized the LEVIR-MCI dataset for experimental validation and performance evaluation.
Main Results
- The DSHA achieved a mean Intersection over Union (mIoU) of 92.28% and an F1 score of 92.50% on the LEVIR-MCI dataset.
- Ablation studies confirmed significant performance improvements attributed to individual DSHA components.
- DSHA demonstrated superior performance compared to existing state-of-the-art methods on the benchmark dataset.
Conclusions
- The proposed DSHA offers a significant advancement in accurate and reliable urban change detection.
- The architecture effectively handles complex scenarios, including multi-scale features and imprecise boundaries.
- DSHA shows strong potential for smart city monitoring applications focused on sustainable urban development.
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