PDF-Unsupervised Visual Domain Adaptation Using Subspace Alignment Basura Fernando Amaury Habrard Marc Sebban and Tinne Tuytelaars KU Leuven ESATPSI iMinds Belgium Laboratoire Hubert Curien UMR rue
In this context our method seeks a domain adaptation solution by learning a mapping function which aligns the source sub space with the target one We show that the
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