Ieee Access Link — Sinha Namrata

Despite promising results, several challenges remain. First, many deep-learning studies rely on laboratory datasets that do not fully represent industrial variability (load changes, sensor placement, environmental noise). Second, there is limited work on computationally efficient architectures suited for edge deployment in resource-constrained monitoring devices. Third, the impact of preprocessing choices (denoising, windowing, transform parameters) on model robustness is not well quantified in the literature.

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#Research #IEEEAccess #Congratulations #WomenInSTEM Despite promising results, several challenges remain

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