Image analysis based on nonnegative/binary matrix factorization

Hinako Asaoka, Kazue Kudo

研究成果: Article査読

4 被引用数 (Scopus)

抄録

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.

本文言語English
論文番号085001
ジャーナルjournal of the physical society of japan
89
8
DOI
出版ステータスPublished - 2020 8月
外部発表はい

ASJC Scopus subject areas

  • 物理学および天文学(全般)

フィンガープリント

「Image analysis based on nonnegative/binary matrix factorization」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル