UAGLNet: Uncertainty-Aggregated Global-Local Fusion Network with Cooperative CNN-Transformer for Building Extraction
Published:Dec 15, 2025 02:59
•1 min read
•ArXiv
Analysis
The article introduces a novel deep learning architecture, UAGLNet, for building extraction. The architecture combines Convolutional Neural Networks (CNNs) and Transformers, leveraging both global and local features. The focus on uncertainty aggregation suggests an attempt to improve robustness and reliability in the extraction process. The source being ArXiv indicates this is a research paper, likely detailing the methodology, experiments, and results of the proposed network.
Key Takeaways
- •UAGLNet is a new deep learning architecture for building extraction.
- •It combines CNNs and Transformers for global and local feature extraction.
- •The architecture incorporates uncertainty aggregation for improved robustness.
- •The paper is likely a research publication on ArXiv.
Reference
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