Image Processing using Pulse-Coupled Neural Networks - Info and Reading Options
By Thomas Lindblad
"Image Processing using Pulse-Coupled Neural Networks" was published by Springer in 2013 - London, the book is classified in Computers genre, it has 154 pages and the language of the book is English.
“Image Processing using Pulse-Coupled Neural Networks” Metadata:
- Title: ➤ Image Processing using Pulse-Coupled Neural Networks
- Author: Thomas Lindblad
- Language: English
- Number of Pages: 154
- Is Family Friendly: Yes - No Mature Content
- Publisher: Springer
- Publish Date: 2013
- Publish Location: London
- Genres: Computers
“Image Processing using Pulse-Coupled Neural Networks” Subjects and Themes:
- Subjects: ➤ Computer Imaging, Vision, Pattern Recognition and Graphics - Image Processing and Computer Vision - Numerical and Computational Physics - Engineering - Computer vision - Biophysics and Biological Physics - Image and Speech Processing Signal - Biomedical engineering - Image processing - Neural networks (computer science)
Edition Specifications:
- Pagination: ix, 152
Edition Identifiers:
- Google Books ID: uOvjBwAAQBAJ
- The Open Library ID: OL37432435M - OL19856880W
- ISBN-13: 9781447136170
- ISBN-10: 1447136179
- All ISBNs: 9781447136170 - 1447136179
AI-generated Review of “Image Processing using Pulse-Coupled Neural Networks”:
Snippets and Summary:
In this volume Thomas Lindblad and Jason Kinser provide a much needed introduction to the topic of PCNNs.
"Image Processing using Pulse-Coupled Neural Networks" Description:
Google Books:
Pulse-coupled neural networks represent a new and exciting advance in image processing research. When exposed to grey scale or colour images they produce a series of binary pulse images which allow the content of the image to be assessed much more accurately than from the original. In this volume Thomas Lindblad and Jason Kinser provide a much needed introduction to the topic of PCNNs. They review the theoretical foundations, and then look at a number of image processing applications including segmentation, edge extraction, texture extraction, object identification, object isolation, motion processing, foveation, noise suppression and image fusion. They also look at the PCNNs ability to process logical arguments and at how to implement it in specialised hardware. It will be of particular interest to researchers and practitioners working in image processing, especially those involved with medical, military or industrial applications. It will also be of interest to graduate-level students.
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- Public Domain: No
- Availability Status: Partially available
- Availability Status for country: US.
- Available Formats: Text is not avialbe, image copy is available.
- Google Books Link: Google Books
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