Applications of Neural Networks in Video Signal Processing
Abstract
Although color TV is an established technology, there are a number of longstanding problems for which neural networks may be suited. Impulse noise is such a problem, and a modular neural network approach is pre(cid:173) sented in this paper. The training and analysis was done on conventional computers, while real-time simulations were performed on a massively par(cid:173) allel computer called the Princeton Engine. The network approach was compared to a conventional alternative, a median filter. Real-time simula(cid:173) tions and quantitative analysis demonstrated the technical superiority of the neural system. Ongoing work is investigating the complexity and cost of implementing this system in hardware.
Cite
Text
Pearson et al. "Applications of Neural Networks in Video Signal Processing." Neural Information Processing Systems, 1990.Markdown
[Pearson et al. "Applications of Neural Networks in Video Signal Processing." Neural Information Processing Systems, 1990.](https://mlanthology.org/neurips/1990/pearson1990neurips-applications/)BibTeX
@inproceedings{pearson1990neurips-applications,
title = {{Applications of Neural Networks in Video Signal Processing}},
author = {Pearson, John C. and Spence, Clay D. and Sverdlove, Ronald},
booktitle = {Neural Information Processing Systems},
year = {1990},
pages = {289-295},
url = {https://mlanthology.org/neurips/1990/pearson1990neurips-applications/}
}