Multi-visual pattern mining algorithm based on variational inference Gaussian mixture and pattern activation response map model.

ABSTRACT: Multi-visual pattern mining plays an important role in image classification, retrieval, and other fields. A multi visual pattern mining algorithm based on variational inference Gaussian mixture model and pattern activation response graph is introduced to address the issues of insufficient frequency and discriminability faced by traditional algorithms. The innovation of this algorithm lies in combining variational inference Gaussian mixture model with pattern activation response graph. The former solves the limitation of manually presetting the number of modes in traditional methods by determining the optimal number of modes to ensure frequency. The latter improves discriminability by capturing key areas of the image, solving the problem of traditional algorithms being difficult to balance

SUBMITTER: Zhang Z 

PROVIDER: S-EPMC12604772 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature