Hierarchical domain adaptation with local feature patterns
Domain adaptation is proposed to generalize learning machines and address performance degradation of models that are trained from one specific source domain but applied to novel target domains. Existing domain adaptation methods focus on transferring holistic features whose discriminability is gener...
Main Authors: | Wen, Jun, Yuan, Junsong, Zheng, Qian, Liu, Risheng, Gong, Zhefeng, Zheng, Nenggan |
---|---|
Other Authors: | School of Electrical and Electronic Engineering |
Format: | Journal Article |
Language: | English |
Published: |
2023
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/164108 |
Similar Items
-
AdaPose: toward cross-site device-free human pose estimation with commodity WiFi
by: Zhou, Yunjiao, et al.
Published: (2025) -
Domain adaption via feature selection on explicit feature map
by: Deng, Wan-Yu, et al.
Published: (2020) -
Feature Adaptation Using Linear Spectro-Temporal Transform for Robust Speech Recognition
by: Nguyen, Duc Hoang Ha, et al.
Published: (2016) -
A general domain specific feature transfer framework for hybrid domain adaptation
by: Wei, Pengfei, et al.
Published: (2020) -
An exemplar-based multi-view domain generalization framework for visual recognition
by: Niu, Li, et al.
Published: (2020)