Learning From Reliable Unlabeled Samples for Semi-Supervised SAR ATR
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DOI: 10.1109/lgrs.2022.3197892
Abstract: Synthetic aperture radar automatic target recognition (SAR ATR) has been suffering from the insufficient labeled samples as the annotation of SAR data is time-consuming. Thus, adding unlabeled samples into training has attracted the attention of… read more here.
Keywords: supervised sar; semi supervised; unlabeled samples; sar atr ... See more keywords