Work

Image Analysis Based on Nonnegative/Binary Matrix Factorization

Year: 2020

Type: article

Abstract: Using nonnegative/binary matrix factorization (NBMF), a matrix can be decomposed into a nonnegative matrix and a binary matrix. Our analysis of facial images, based on NBMF and using the Fujitsu Digital Annealer, leads to successful image reconstruction and image classification. The NBMF algorithm converges in fewer iterations than those required for the convergence of nonnegative matrix factorization (NMF), although both techniques perform comparably in image classification.

Source: Journal of the Physical Society of Japan

DOI: 10.7566/jpsj.89.085001

Authors: Hinako Asaoka, Kazue Kudo

Institution: Ochanomizu University

Language: English

Topic: Face and Expression Recognition

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: Japan Society for the Promotion of Science

Award: Combinatorial optimization by quantum computing: Control of quantum dynamics for efficient calculation