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Sewer-Transformer-ML is developed, a hierarchical vision Transformer with multi-level feature fusion together with two lightweight architectures, Sewer-MobileNet-ML and Sewer-Mobile-TransNet, for resource-constrained inspection scenarios and provides a computational basis for automated sewer inspection, lightweight model design, and adaptation across civil infrastructure inspection platforms.
A leading-order effective field links empirical dynamics to neural computation, revealing how human-AI interactions exhibit reproducible and interpretable patterns.
