Image Restoration Using RBM
Image restoration is a critical task in computer vision, aiming to recover degraded images caused by noise, missing pixels, or corruption. Restricted Boltzmann Machines (RBMs), a type of unsupervised neural network, have gained popularity for their ability to learn hidden representations and restore images effectively. This paper provides a review of existing research and projects related to image restoration using RBMs and other deep learning techniques. It highlights the key approaches, algorithms, and outcomes in this field, providing a comparative perspective on their effectiveness
Authors
- Vrushali Kondhalkar (ORCID: https://orcid.org/0000-0003-1664-6722)
Institutions
- Myanmar Institute of Theology (MM)
Publication Details
- Journal
- International Journal for Research in Applied Science and Engineering Technology
- Published
- 2025-05-28
- DOI
- https://doi.org/10.22214/ijraset.2025.71087
- Primary Topic
- Generative Adversarial Networks and Image Synthesis
- Type
- article
- Field-Weighted Citation Impact
- 0.00