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Frontiers of Computer Science

ISSN 2095-2228

ISSN 2095-2236(Online)

CN 10-1014/TP

邮发代号 80-970

2019 Impact Factor: 1.275

Frontiers of Computer Science  2023, Vol. 17 Issue (1): 171308   https://doi.org/10.1007/s11704-022-1283-6
  本期目录
Self-adaptive label filtering learning for unsupervised domain adaptation
Qing TIAN1,2(), Heyang SUN1, Shun PENG1, Tinghuai MA1,2
1. School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing 210044, China
2. Engineering Research Center of Digital Forensics, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing 210044, China
 全文: PDF(3924 KB)   HTML
收稿日期: 2021-05-25      出版日期: 2022-03-01
Corresponding Author(s): Qing TIAN   
 引用本文:   
. [J]. Frontiers of Computer Science, 2023, 17(1): 171308.
Qing TIAN, Heyang SUN, Shun PENG, Tinghuai MA. Self-adaptive label filtering learning for unsupervised domain adaptation. Front. Comput. Sci., 2023, 17(1): 171308.
 链接本文:  
https://academic.hep.com.cn/fcs/CN/10.1007/s11704-022-1283-6
https://academic.hep.com.cn/fcs/CN/Y2023/V17/I1/171308
Fig.1  
Fig.2  
PCA JDA JGSA DICD DGA-DA SALFL
C A 36.78 45.28 53.07 51.96 52.15 56.22
C W 31.98 41.89 48.21 47.68 47.34 60.77
C D 37.54 45.42 48.60 46.21 45.84 59.05
A C 34.82 39.26 41.66 41.66 41.36 45.95
A W 35.93 37.88 44.91 38.49 38.38 50.53
A D 27.52 39.04 45.15 38.65 38.34 48.34
W C 26.34 31.65 33.47 33.68 33.25 37.03
W A 31.44 32.73 40.87 41.20 41.56 42.33
W D 77.87 89.67 88.69 91.17 90.04 93.79
D C 29.52 30.63 30.50 34.08 33.60 33.67
D A 31.69 33.27 38.73 33.87 33.56 37.35
D W 75.80 89.59 93.74 93.76 93.26 94.14
Average 39.77 46.36 50.63 49.37 49.06 54.93
Tab.1  
1 S Wold , K Esbensen , P Geladi . Principal component analysis. Chemometrics and Intelligent Laboratory Systems, 1987, 2( 1−3): 37– 52
2 M Long, G Ding, J Wang, J Sun, Y Guo, P S Yu. Transfer sparse coding for robust image representation. In: Proceedings of 2013 IEEE Conference on Computer Vision and Pattern Recognition. 2013, 407– 414
3 J Zhang, W Li, P Ogunbona. Joint geometrical and statistical alignment for visual domain adaptation. In: Proceedings of 2017 IEEE Conference on Computer Vision and Pattern Recognition. 2017, 5150– 5158
4 S Li , S Song , G Huang , Z Ding , C Wu . Domain invariant and class discriminative feature learning for visual domain adaptation. IEEE Transactions on Image Processing, 2018, 27( 9): 4260– 4273
5 L Luo , L Chen , S Hu , Y Lu , X Wang . Discriminative and geometry-aware unsupervised domain adaptation. IEEE Transactions on Cybernetics, 2020, 50( 9): 3914– 3927
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