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Topography-Enhanced Multilevel Residual Attention U-Net Model for Sea Ice Concentration Spatial Super-Resolution Prediction
Published 2025-01-01“…Experimental results indicate that, in the pan-Arctic region, TE-MRAU-Net outperforms other models in various evaluation metrics and spatial distribution reconstruction. For the 5× SR prediction task, the model achieves a mean absolute error of 0.0049, a root-mean-square error of 0.0081, a correlation coefficient (<inline-formula><tex-math notation="LaTeX">$r$</tex-math></inline-formula>) of 0.9993, a peak signal-to-noise ratio of 40.21 dB, a structural similarity index measure of 0.9764, a balanced accuracy of 0.9428, a mean opinion score of 4.63, and a subjective image quality assessment of 9.75, greatly enhancing the model’s ability to capture detailed SIC features.…”
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Environmental cues in different host niches shape the survival fitness of Staphylococcus aureus
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Strategic planning of municipalities’ development under post-growth scenarios
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Construction and efficiency analysis of an embedded system-based verification platform for edge computing
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Asteroids Exploration Trajectory Optimal Design with Differential Evolution Based on Mixed Coding
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Inventory Tracking for Unstructured Environments via Probabilistic Reasoning
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Dense-TNT: Efficient Vehicle Type Classification Neural Network Using Satellite Imagery
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Modeling and Proportional-Integral State Feedback Control of Fully Parallel Grid-Connected Inverters
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Usefulness of mobile learning (M-learning) in learning foreign languages
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Challenges of 4IR implementation in post offices in developing countries: A case study of South Africa
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A statistical framework for modelling migration corridors
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Charting resilience: a typology of food self-sufficiency in OECD nations
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A systematic survey: role of deep learning-based image anomaly detection in industrial inspection contexts
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Socio-economic Empowerment of Women through Self Help Groups Nagaland, India
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