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Learning graph-Fourier spectra of textured surface images for defect localization
This paper introduces an approach based on graph Fourier analysis to automatically identify defective images, as well as crucial graph Fourier coefficients that inform the defects in images amidst highly textured backgrounds.
In-situ surface porosity prediction in DED (directed energy deposition) printed SS316L parts using multimodal sensor fusion
Adapting an explainable AI method in LIME (Local Interpretable Model-Agnostic Explanations), certain high-frequency waveform signatures of AE are to be attributed to two major pathways for pore formation in a DED process, namely, spatter events and insufficient fusion between adjacent printing tracks from low heat input.
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