# Image Analysis Based on Nonnegative/Binary Matrix Factorization

arXiv: https://arxiv.org/abs/2007.00889 · HTML: https://mlsanity.com/paper/2007.00889/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Jul 2020.

## Built on by (most cited first, 3 of 3)

- [Nonnegative/Binary Matrix Factorization for Image Classification using Quantum Annealing](https://mlsanity.com/paper/2311.01028/) (2023)
- [Subsampling Factorization Machine Annealing](https://mlsanity.com/paper/2508.08778/) (2025)
- [Collaborative filtering based on nonnegative/binary matrix factorization](https://mlsanity.com/paper/2410.10381/) (2024)

## Abstract (arXiv)

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.