SAIT: Harnessing Sparse Annotations and Intrinsic Tasks for Semisupervised Aeroengine Defect Segmentation
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DOI: 10.1109/tii.2024.3396550
Abstract: In aeroengine maintenance, endoscopic imaging serves as a crucial tool for detecting blade defects and evolves toward intelligence driven by computer vision technology. Currently, supervised-learning-based defect segmentation methods mainly rely on extensive pixel-level annotations, making… read more here.
Keywords: pixel level; segmentation; harnessing sparse; sait harnessing ... See more keywords