atopic-rhinitis
发表于 2025-3-28 15:03:16
http://reply.papertrans.cn/29/2825/282486/282486_41.png
xanthelasma
发表于 2025-3-28 20:53:25
http://reply.papertrans.cn/29/2825/282486/282486_42.png
nonplus
发表于 2025-3-29 00:21:33
https://doi.org/10.1007/978-3-031-34398-8rning and DA techniques, and we study their generalization properties to parts from unseen classes when they are learned from a limited number of domains and example images. One of our conclusions is that, for a majority of the domains, part annotations transfer well, and that, performance of the se
Middle-Ear
发表于 2025-3-29 03:12:43
Geodesic Flow Kernel and Landmarks: Kernel Methods for Unsupervised Domain Adaptation hand, we propose . of a kernel that discriminatively combines multiple base GFKs to model the source and the target domains at fine-grained granularities. In particular, each base kernel pivots on a different set of landmarks—the most useful data instances that reveal the similarity between the sou
财政
发表于 2025-3-29 08:41:59
http://reply.papertrans.cn/29/2825/282486/282486_45.png
majestic
发表于 2025-3-29 12:31:13
Correlation Alignment for Unsupervised Domain Adaptationl but the number and dimensionality of target examples are very high. The resulting CORAL Linear Discriminant Analysis (CORAL-LDA)outperforms LDA by a large margin on standard domain adaptation benchmarks. Finally, we extend CORAL to learn a nonlinear transformation that aligns correlations of layer
配偶
发表于 2025-3-29 16:37:46
http://reply.papertrans.cn/29/2825/282486/282486_47.png
pantomime
发表于 2025-3-29 23:31:45
http://reply.papertrans.cn/29/2825/282486/282486_48.png
GENRE
发表于 2025-3-30 00:12:55
http://reply.papertrans.cn/29/2825/282486/282486_49.png
Middle-Ear
发表于 2025-3-30 07:55:58
Generalizing Semantic Part Detectors Across Domainsrning and DA techniques, and we study their generalization properties to parts from unseen classes when they are learned from a limited number of domains and example images. One of our conclusions is that, for a majority of the domains, part annotations transfer well, and that, performance of the se