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Canadian Journal of Remote Sensing
Journal canadien de télédétection
Volume 49, 2023 - Issue 1
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Research Article

Sensitivity Analysis of Parameters of U-Net Model for Semantic Segmentation of Silt Storage Dams from Remote Sensing Images

Analyse de sensibilité des paramètres du modèle U-Net pour la segmentation sémantique de barrages de retenue en limon à partir d’images de télédétection

ORCID Icon, , , &
Article: 2178834 | Received 12 Aug 2022, Accepted 06 Feb 2023, Published online: 06 Mar 2023

Figures & data

Figure 1. Location of the watersheds of Hulu River and Lanni River.

Figure 1. Location of the watersheds of Hulu River and Lanni River.

Figure 2. Examples of image slices.

Figure 2. Examples of image slices.

Figure 3. Structure of U-Net (source: https://www.jianshu.com/p/0bb14fb7de62).

Figure 3. Structure of U-Net (source: https://www.jianshu.com/p/0bb14fb7de62).

Figure 4. Visualized silt storage dams of original images (a), segmented by U-Net with different input sizes of 288 × 288 (b), 384 × 384 (c), 480 × 480 (d), and 576 × 576 (e), and ground truth of silt storage dams (f).

Figure 4. Visualized silt storage dams of original images (a), segmented by U-Net with different input sizes of 288 × 288 (b), 384 × 384 (c), 480 × 480 (d), and 576 × 576 (e), and ground truth of silt storage dams (f).

Table 1. Accuracies of silt storage dams semantically segmented by U-Net with different input sizes.

Figure 5. Visualized silt storage dams of original images (a) and segmented by U-Net with batch sizes of 2 (b), 3 (c), and 4 (d).

Figure 5. Visualized silt storage dams of original images (a) and segmented by U-Net with batch sizes of 2 (b), 3 (c), and 4 (d).

Table 2. Accuracies of silt storage dams segmented by U-Net with different batch sizes.

Figure 6. Visualized silt storage dams of original images (a and c) and segmented by U-Net model using Datasets 1 (b), 2 (d), and 3 (e).

Figure 6. Visualized silt storage dams of original images (a and c) and segmented by U-Net model using Datasets 1 (b), 2 (d), and 3 (e).

Table 3. Accuracies of silt storage dams segmented by U-Net with different sample sizes.

Figure 7. Loss curves obtained by U-Net based on Datasets 1 (a), 2 (b), and 3 (c).

Figure 7. Loss curves obtained by U-Net based on Datasets 1 (a), 2 (b), and 3 (c).

Table 4. Averages and standard deviations (SD) of accuracies of silt storage dams segmented by U-Net and FCN with input size of 576 × 576, batch size of 4, and Dataset 3 for 30 repeated trials.

Table 5. Comparison of F1, P, and MIoU obtained from the labeling functions and the label model with the images of input size of 576 × 576 and batch size of 4.