Data-driven structural damage detection approach for Digital twin-Structural health monitoring
As part of the project activity funded by the Newton Fund Institutional Links through the U.K. Department of Business, Energy, and Industrial Strategy and managed by the British Council under Grant 429715093, Research paper ” Data-Driven Structural Health Monitoring using feature Fusion and Hybrid Deep Learning ” was accepted for publication in Q1 journal “IEEE … Continue reading Data-driven structural damage detection approach for Digital twin-Structural health monitoring
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