Quantum-Inspired Acceleration for Image Reconstruction on Ising Machines
Journal
2024 IEEE International Conference on Quantum Computing and Engineering (QCE)
Journal Volume
2
Start Page
547
End Page
548
Date Issued
2024-09-15
Author(s)
Abstract
The study investigates a quantum-inspired approach to image reconstruction using Ising machines and demonstrates its significant improvements over the contrastive divergence method in Restricted Boltzmann Machines training and the quality of image reconstruction on the MINST digits and fashion datasets.
Subjects
Generative AI
Image reconstruction
Ising machines
Quantum-inspired
Restricted Boltzmann Machines
Publisher
IEEE
Type
conference paper