.png){kind=icon}
Return
Learning with Euler non-negative representation for robust pattern analysis
.png){kind=icon}
PRE
AI
DOI：10.1016/j.eswa.2026.132229.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
• Euler non-negative representation captures nonlinearity with Euler transformation. • Euler non-negative collaborative representation achieves both nonlinearity and efficiency. • Robust Newton-based solver handles constant, linear, and random noise.
Keywords:
Euler non-negative representation
Non-negative collaborative representation
Robust pattern analysis
Newton-based solver
Pattern recognition
Journal
IF:
7.5
Papers:
3.0W
Citations:
10.2W
Organization
Cited Papers
From few to many: illumination cone models for face recognition under variable lighting and pose
PREAI
ShareSaveShareSave
ShareSaveEfficient classification with sparsity augmented collaborative representation.png)
PATTERN RECOGNITION
PATTERN RECOGNITIONIF7.6
PREAI
ShareSaveShareSaveShareSaveShareSave
View more