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- Title
Three-Stage MPViT-DeepLab Transfer Learning for Community-Scale Green Infrastructure Extraction.
- Authors
Li, Hang; Zhao, Shengjie; Deng, Hao
- Abstract
The extraction of community-scale green infrastructure (CSGI) poses challenges due to limited training data and the diverse scales of the targets. In this paper, we reannotate a training dataset of CSGI and propose a three-stage transfer learning method employing a novel hybrid architecture, MPViT-DeepLab, to help us focus on CSGI extraction and improve its accuracy. In MPViT-DeepLab, a Multi-path Vision Transformer (MPViT) serves as the feature extractor, feeding both coarse and fine features into the decoder and encoder of DeepLabv3+, respectively, which enables pixel-level segmentation of CSGI in remote sensing images. Our method achieves state-of-the-art results on the reannotated dataset.
- Subjects
GREEN infrastructure; TRANSFORMER models; REMOTE sensing; IMAGE segmentation
- Publication
Information (2078-2489), 2024, Vol 15, Issue 1, p15
- ISSN
2078-2489
- Publication type
Article
- DOI
10.3390/info15010015