Classification with Incoherent Kernel Dictionary Learning
arXiv:2307.08796v11 citationsh-index: 19Has Code
Originality Synthesis-oriented
AI Analysis
This is an incremental improvement for classification tasks using dictionary learning methods.
The authors tackled classification by developing a kernel version of incoherent dictionary learning and improving the AK-SVD algorithm, achieving results tested on popular databases.
In this paper we present a new classification method based on Dictionary Learning (DL). The main contribution consists of a kernel version of incoherent DL, derived from its standard linear counterpart. We also propose an improvement of the AK-SVD algorithm concerning the representation update. Our algorithms are tested on several popular databases of classification problems.