Schroedinger Eigenmaps for Dimensionality Reduction and Image Classification

Abstract

In this paper, we propose a Schroedinger Eigenmaps (SE) manifold learning and dimensionality reduction method on glaucoma image classification. The visualization of binary image recognition three dimensional electronic cloud image on the retinal fundus dataset shows that after quantum circuit diagram transformation, the recognition performance of the image data in the Schroedinger Eigenmaps (SE) manifold learning dimensionality reduction spatial distribution has been significantly improved for binary image classification.