凶残 发表于 2025-3-25 07:08:15

http://reply.papertrans.cn/99/9838/983719/983719_21.png

RACE 发表于 2025-3-25 08:31:26

http://reply.papertrans.cn/99/9838/983719/983719_22.png

食料 发表于 2025-3-25 14:34:52

http://reply.papertrans.cn/99/9838/983719/983719_23.png

seroma 发表于 2025-3-25 16:50:11

http://reply.papertrans.cn/99/9838/983719/983719_24.png

Melanocytes 发表于 2025-3-25 21:02:43

http://reply.papertrans.cn/99/9838/983719/983719_25.png

PIZZA 发表于 2025-3-26 03:50:21

978-3-031-79170-3Springer Nature Switzerland AG 2022

进取心 发表于 2025-3-26 05:24:17

http://reply.papertrans.cn/99/9838/983719/983719_27.png

Eulogy 发表于 2025-3-26 11:56:50

2153-1056 n many situations huge volumes of unlabeled data can be and often are generated and available, the cost of acquiring data labels remains high. Transfer learning (TL), and in particular domain adaptation (DA), has emerged as an effective solution to overcome the burden of annotation, exploiting the u

Eeg332 发表于 2025-3-26 14:01:15

http://reply.papertrans.cn/99/9838/983719/983719_29.png

Pericarditis 发表于 2025-3-26 18:58:44

http://reply.papertrans.cn/99/9838/983719/983719_30.png
页: 1 2 [3] 4
查看完整版本: Titlebook: Visual Domain Adaptation in the Deep Learning Era; Gabriela Csurka,Timothy M. Hospedales,Tatiana Tomm Book 2022 Springer Nature Switzerlan