Opto-Electronic Engineering, Volume. 52, Issue 3, 240231(2025)
Fusion of dynamic features enhances remote sensing building segmentation
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Fig. 7. Accuracy diagram of evaluation index of the improved model
Table 1. Ablation experiments results
View tableView in ArticleTable 1. Ablation experiments results
Number A B C D Precision/% Recall/% F1-Score/% mIoU/% 1 × × × × 82.32 75.58 81.64 74.35 2 √ × × × 84.14 77.48 83.68 77.51 3 × √ × × 84.45 76.96 82.94 76.23 4 × × √ × 85.56 78.95 83.45 78.51 5 × × × √ 86.54 79.45 83.96 80.48 6 × × √ √ 87.19 82.49 84.59 81.74 7 √ √ × × 88.94 84.53 85.61 82.48 8 √ × √ √ 91.85 83.89 86.95 81.87 9 × √ √ √ 91.25 86.57 88.91 82.36 10 √ √ √ √ 94.45 88.86 90.21 86.83
Table 2. Precision comparison results of various algorithms
View tableView in ArticleTable 2. Precision comparison results of various algorithms
Arithmetic Precision/% Recall% F1-Score/% mIoU/% Time/(min/Epoch) UNet 87.85 86.87 86.95 82.64 4.0 FCN 86.46 85.76 84.63 79.62 4.5 SegNet 89.39 88.68 87.25 83.46 3.5 DeepLabv3+ 82.32 75.58 81.64 74.35 5.0 Our Methods 94.45 88.86 90.21 86.83 2.5
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Zhenjiu Xiao, Hao Tian, Jiehao Zhang, Haicheng Qu. Fusion of dynamic features enhances remote sensing building segmentation[J]. Opto-Electronic Engineering, 2025, 52(3): 240231
Paper Information
Category: Article
Received: Sep. 30, 2024
Accepted: Jan. 8, 2025
Published Online: May. 22, 2025
The Author Email: Hao Tian (田昊)
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