conference paper

A Feature Selection Approach to Visual Domain Adaptation in Classification

Rakesh Kumar Sanodiya^a, Debdeep Paul^b, Leehter Yao^a✉, Jimson Mathew^b, Aparna Juhi^c

^aNational Taipei University of Technology, Taipei, 10608, Taiwan
^bIndian Institute of Technology Patna, Patna, India
^cNational Institute of Technology Patna, Patna, India
✉Corresponding author

Lecture notes in computer science Springer Science+Business Media2020-01-01 7 citations15 references

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TL;DRA new feature selection based visual domain adaptation (FSVDA) method which uses particle swarm optimization (PSO), where the MEDA method is considered as a fitness function that leads to automatically select a good subset of features over both the domains. (Semantic Scholar)

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A Feature Selection Approach to Visual Domain Adaptation in Classification

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