River Surface Space–Time Image Velocimetry Based on Dual-Channel Residual Network
Abstract
:1. Introduction
2. Materials and Methods
2.1. Basic Principle of STIV
2.2. Dual-Channel Residual Network Model
2.3. Adaptive Threshold Sobel Operator
3. Model Training and Fusion Coefficient Determination
3.1. Dataset Construction
3.2. Determination of Fusion Coefficient
4. Experiments and Discussions
4.1. Experimental Platform and Evaluation Method
4.2. MOT Detection Comparison Experiments
4.3. Surface Velocity Comparison Experiments
4.3.1. Experimental Settings of Surface Velocity Measurement
4.3.2. Test 1: Sunny Day at Panzhihua Station
4.3.3. Test 2: Rainy Day at Panzhihua Station
4.3.4. Test 3: Cloudy Day at Hebian Station
4.4. Vertical Average Velocity Comparison Experiment
4.4.1. Experimental Settings of Vertical Average Velocity Measurement
4.4.2. Experimental Results
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Scenario | Training Set (Piece) | Test Set (Piece) |
---|---|---|
normal | 16,800 | 8400 |
vortex | 8400 | 3360 |
flare | 8400 | 3360 |
obstacle | 8400 | 3360 |
rain | 8400 | 3360 |
Regression Model | Dual-Channel | Edge-Channel | Gray-Channel |
---|---|---|---|
MAE | 0.64 | 0.87 | 0.82 |
SD | 0.71 | 1.01 | 1.43 |
Scenario | Dual-Channel | Edge-Channel | Gray-Channel |
---|---|---|---|
normal | 0.41 | 0.61 | 0.65 |
vortex | 1.10 | 1.14 | 1.15 |
flare | 0.57 | 0.81 | 0.82 |
obstacle | 0.33 | 0.34 | 0.44 |
rain | 1.17 | 1.50 | 1.36 |
Number | Starting Distance (m) | FFT (°) | DCResNet (°) | Label Value (°) | AE (°) | |
---|---|---|---|---|---|---|
FFT | DCResNet | |||||
1 | 45 | 81.45 | 80.30 | 80.89 | 0.56 | 0.59 |
2 | 65 | 81.97 | 82.22 | 82.20 | 0.23 | 0.02 |
3 | 75 | 80.57 | 80.63 | 80.80 | 0.23 | 0.17 |
4 | 85 | 80.01 | 80.35 | 80.48 | 0.47 | 0.13 |
5 | 95 | 78.95 | 78.62 | 78.80 | 0.15 | 0.18 |
6 | 115 | 77.39 | 77.48 | 77.52 | 0.13 | 0.04 |
7 | 130 | 75.43 | 74.56 | 74.45 | 0.98 | 0.11 |
8 | 145 | 68.10 | 66.30 | 66.10 | 2.00 | 0.20 |
9 | 160 | 18.55 | 41.50 | 43.39 | 24.84 | 1.89 |
Number | Starting Distance (m) | FFT (m/s) | DCResNet (m/s) | Label Value (m/s) | RE (%) | |
---|---|---|---|---|---|---|
FFT | DCResNet | |||||
1 | 45 | 2.48 | 2.18 | 2.33 | 6.44 | 6.44 |
2 | 65 | 3.91 | 4.05 | 4.03 | 2.98 | 0.50 |
3 | 75 | 3.92 | 3.94 | 4.01 | 2.24 | 1.75 |
4 | 85 | 4.15 | 4.30 | 4.36 | 4.82 | 1.38 |
5 | 95 | 4.16 | 4.04 | 4.11 | 1.22 | 1.70 |
6 | 115 | 4.29 | 4.32 | 4.34 | 1.15 | 0.46 |
7 | 130 | 4.20 | 3.95 | 3.92 | 7.14 | 0.77 |
8 | 145 | 3.08 | 2.96 | 2.79 | 10.39 | 6.09 |
9 | 160 | 0.44 | 1.15 | 1.25 | 64.8 | 8.00 |
Number | Starting Distance (m) | FFT (°) | DCResNet (°) | Label Value (°) | AE (°) | |
---|---|---|---|---|---|---|
FFT | DCResNet | |||||
1 | 50 | 23.95 | 77.11 | 78.02 | 54.07 | 0.91 |
2 | 60 | 80.44 | 79.69 | 80. 01 | 0.43 | 0.32 |
3 | 75 | 80.42 | 80.62 | 80.78 | 0.36 | 0.16 |
4 | 85 | 79.31 | 78.60 | 78.31 | 1.00 | 0.29 |
5 | 95 | 78.50 | 79.03 | 78.75 | 0.25 | 0.28 |
6 | 105 | 77.02 | 77.39 | 77.21 | 0.19 | 0.18 |
7 | 120 | 74.55 | 75.02 | 74.68 | 0.13 | 0.34 |
8 | 140 | 76.12 | 67.59 | 65.34 | 10.78 | 2.25 |
9 | 160 | 23.30 | 39.12 | 37.25 | 13.95 | 1.87 |
Number | Starting Distance (m) | FFT (m/s) | DCResNet (m/s) | Label Value (m/s) | RE (%) | |
---|---|---|---|---|---|---|
FFT | DCResNet | |||||
1 | 50 | 0.20 | 2.06 | 2.21 | 90.95 | 6.79 |
2 | 60 | 3.28 | 3.04 | 3.16 | 3.80 | 3.80 |
3 | 75 | 3.66 | 3.75 | 3.81 | 3.94 | 1.57 |
4 | 85 | 3.69 | 3.47 | 3.37 | 9.50 | 2.97 |
5 | 95 | 3.92 | 4.12 | 4.01 | 2.24 | 2.74 |
6 | 105 | 3.80 | 3.93 | 3.87 | 1.81 | 1.55 |
7 | 120 | 3.71 | 3.84 | 3.74 | 0.80 | 2.67 |
8 | 140 | 4.75 | 2.85 | 2.56 | 85.55 | 11.33 |
9 | 160 | 0.56 | 1.06 | 0.99 | 43.43 | 7.07 |
Number | Starting Distance (m) | FFT (°) | DCResNet (°) | Label Value (°) | AE (°) | |
---|---|---|---|---|---|---|
FFT | DCResNet | |||||
1 | 2 | 81.30 | 84.87 | 85.24 | 3.94 | 0.37 |
2 | 4 | 85.49 | 86.24 | 86.56 | 1.07 | 0.32 |
3 | 6 | 86.66 | 86.65 | 86.47 | 0.19 | 0.18 |
4 | 8 | 86.11 | 86.15 | 85.9 | 0.21 | 0.25 |
5 | 10 | 85.69 | 86.02 | 86.05 | 0.36 | 0.03 |
6 | 12 | 85.07 | 85.61 | 85.31 | 0.24 | 0.30 |
7 | 14 | 84.66 | 85.10 | 84.91 | 0.25 | 0.19 |
8 | 16 | 81.75 | 81.65 | 84.32 | 2.57 | 2.67 |
9 | 18 | 83.67 | 83.56 | 83.88 | 0.21 | 0.32 |
Number | Starting Distance (m) | FFT (m/s) | DCResNet (m/s) | Label Value (m/s) | RE (%) | |
---|---|---|---|---|---|---|
FFT | DCResNet | |||||
1 | 2 | 0.51 | 0.87 | 0.94 | 45.74 | 7.45 |
2 | 4 | 1.65 | 1.98 | 2.16 | 23.61 | 8.33 |
3 | 6 | 2.17 | 2.17 | 2.06 | 5.34 | 5.34 |
4 | 8 | 2.22 | 2.25 | 2.11 | 5.21 | 6.64 |
5 | 10 | 2.35 | 2.54 | 2.56 | 8.20 | 0.78 |
6 | 12 | 2.34 | 2.63 | 2.46 | 4.88 | 6.91 |
7 | 14 | 2.43 | 2.64 | 2.54 | 4.33 | 3.94 |
8 | 16 | 1.72 | 1.7 | 2.50 | 31.20 | 32.00 |
9 | 18 | 2.61 | 2.57 | 2.70 | 3.33 | 4.81 |
Number | Starting Distance (m) | FFT (°) | DCResNet (°) | Label Value (°) | AE (°) | |
---|---|---|---|---|---|---|
FFT | DCResNet | |||||
1 | 55 | 82.71 | 82.91 | 82.60 | 0.11 | 0.31 |
2 | 65 | 81.66 | 81.72 | 81.54 | 0.12 | 0.18 |
3 | 90 | 80.61 | 80.83 | 80.69 | 0.08 | 0.14 |
4 | 105 | 79.32 | 79.53 | 79.40 | 0.08 | 0.13 |
5 | 120 | 78.18 | 78.52 | 78.38 | 0.20 | 0.14 |
6 | 135 | 77.55 | 77.32 | 77.41 | 0.14 | 0.09 |
7 | 155 | 73.10 | 70.21 | 69.81 | 3.29 | 0.40 |
8 | 165 | 70.52 | 58.45 | 56.80 | 13.72 | 1.65 |
9 | 175 | 72.02 | 37.69 | 38.20 | 33.82 | 0.51 |
Number | Starting Distance (m) | FFT (m/s) | DCResNet (m/s) | Current Meter (m/s) | RE (%) | |
---|---|---|---|---|---|---|
FFT | DCResNet | |||||
1 | 55 | 3.12 | 3.21 | 3.22 | 3.11 | 0.31 |
2 | 65 | 3.22 | 3.24 | 3.40 | 5.29 | 4.71 |
3 | 90 | 4.00 | 4.10 | 4.22 | 5.21 | 2.84 |
4 | 105 | 4.05 | 4.13 | 4.12 | 1.70 | 0.24 |
5 | 120 | 4.23 | 4.35 | 4.20 | 0.71 | 3.57 |
6 | 135 | 4.44 | 4.36 | 4.56 | 2.63 | 4.39 |
7 | 155 | 2.66 | 3.13 | 3.35 | 20.60 | 6.57 |
8 | 165 | 3.73 | 1.81 | 1.87 | 99.47 | 3.21 |
9 | 175 | 3.92 | 0.98 | 1.10 | 256.36 | 10.91 |
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Share and Cite
Gao, L.; Zhang, Z.; Chen, L.; Li, H. River Surface Space–Time Image Velocimetry Based on Dual-Channel Residual Network. Appl. Sci. 2025, 15, 5284. https://doi.org/10.3390/app15105284
Gao L, Zhang Z, Chen L, Li H. River Surface Space–Time Image Velocimetry Based on Dual-Channel Residual Network. Applied Sciences. 2025; 15(10):5284. https://doi.org/10.3390/app15105284
Chicago/Turabian StyleGao, Ling, Zhen Zhang, Lin Chen, and Huabao Li. 2025. "River Surface Space–Time Image Velocimetry Based on Dual-Channel Residual Network" Applied Sciences 15, no. 10: 5284. https://doi.org/10.3390/app15105284
APA StyleGao, L., Zhang, Z., Chen, L., & Li, H. (2025). River Surface Space–Time Image Velocimetry Based on Dual-Channel Residual Network. Applied Sciences, 15(10), 5284. https://doi.org/10.3390/app15105284