Year: 2025
Type: article
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
Author: Vrushali Kondhalkar
Institution: Massachusetts Institute of Technology
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4410825387