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Learning adaptive geometry for unsupervised domain adaptation
Baoyao Yang,
Pong Chi Yuen
*
*
Corresponding author for this work
Department of Computer Science
Research output
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Contribution to journal
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Journal article
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peer-review
18
Citations (Scopus)
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Dive into the research topics of 'Learning adaptive geometry for unsupervised domain adaptation'. Together they form a unique fingerprint.
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Keyphrases
Adaptive Geometry
100%
Learning Adaptive
100%
Unsupervised Domain Adaptation
100%
Target Domain
25%
Recognition Task
25%
Adversarial Learning
25%
Source Domain
25%
Data Distribution
25%
Effective Approach
25%
Data Representation
25%
Domain Adaptation Method
25%
Target Labels
25%
Unified Criterion
25%
Learning Techniques
25%
Invalid
25%
Modes of Variability
25%
Geometry-aware
25%
Dataset Bias
25%
Source Geometry
25%
Dual-stream Network
25%
Variation Degree
25%
Cross-dataset Recognition
25%
Target Geometry
25%
Label Space
25%
Geometry Learning
25%
Geometry Structure
25%
Engineering
Experimental Result
100%
Good Performance
100%
Effective Approach
100%
Learning Technique
100%
Test Dataset
100%
Data Representation
100%
Computer Science
Adaptive Learning
100%
Unsupervised Domain Adaptation
100%
Experimental Result
33%
Good Performance
33%
Data Distribution
33%
Effective Approach
33%
Data Representation
33%
Learning Technique
33%