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

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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
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article

Image Restoration Using RBM

Vrushali Kondhalkar
International Journal for Research in Applied Science and Engineering Technology
Generative Adversarial Networks and Image Synthesis
article

Image Restoration Using RBM

Vrushali Kondhalkar
article en

Abstract

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

International Journal for Research in Applied Science and Engineering TechnologyVol. 13(5)
Myanmar Institute of Theology (MM)
Peace, Justice and strong institutions
Openalex Percentile: Top 90%
Generative Adversarial Networks and Image Synthesis
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