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Published in 2025 at "IEEE Access"
DOI: 10.1109/access.2024.3520503
Abstract: This article starts from the perspective of breaking the integrity of the feature matrix, dividing it into retained and sacrificed parts, and using the sacrificed parts to strengthen the retained parts. We propose SpiltAtt and…
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Keywords:
feature learning;
grained feature;
improve fine;
fine grained ... See more keywords