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Unsupervised domain adaptation with structural attribute learning networks

NEUROCOMPUTING, (2020): 96-105

Cited by: 0|Views25
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Abstract

Domain adaptation aims at improving the performance on an unknown target domain by transferring the knowledge learned from a related source domain. In this paper, we propose a structural attribute learning network (SAL Net) which can learn transferable domain-invariance features based on the attribute learning. Our proposed SAL Net can le...More

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