NIST · ИТ · 83b9d5558b3d8252ebc1
Sparse Embedding-based Domain Adaptation for Object Recognition
Domain adaptation algorithms aim at handling the shift between source and target domains. A classifier is trained on images from the source domain; and the classifier recognizes objects in images from the target domain. In this paper, we present a joint
NIST · ИТОфициальный источник · 2013-12-08
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"title_en": "Sparse Embedding-based Domain Adaptation for Object Recognition",
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"date": "2013-12-08",
"date_original": "December 8, 2013",
"url": "https://www.nist.gov/publications/sparse-embedding-based-domain-adaptation-object-recognition",
"source": "NIST Publications",
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"authors_en": "P J. Phillips , Jingjing Zheng, Rama Chellappa",
"abstract_excerpt_en": "Domain adaptation algorithms aim at handling the shift between source and target domains. A classifier is trained on images from the source domain; and the classifier recognizes objects in images from the target domain. In this paper, we present a joint",
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"title_en": "Sparse Embedding-based Domain Adaptation for Object Recognition",
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"authors_en": "P J. Phillips , Jingjing Zheng, Rama Chellappa",
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