Image Processing using Pulse-Coupled Neural Networks - Info and Reading Options
Applications in Python
By Thomas Lindblad
"Image Processing using Pulse-Coupled Neural Networks" was published by Springer Berlin Heidelberg in 2013 - Berlin, Heidelberg, it has 238 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: 238
- Publisher: Springer Berlin Heidelberg
- Publish Date: 2013
- Publish Location: Berlin, Heidelberg
“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:
- Format: [electronic resource] :
- Pagination: ➤ XXIV, 238 p. 142 illus., 9 illus. in color.
Edition Identifiers:
- The Open Library ID: OL27044918M - OL19856880W
- ISBN-13: 9783642368776
- All ISBNs: 9783642368776
AI-generated Review of “Image Processing using Pulse-Coupled Neural Networks”:
"Image Processing using Pulse-Coupled Neural Networks" Table Of Contents:
- 1- Biological Models
- 2- Programming in Python
- 3- NumPy, SciPy and Python Image Library
- 4- The PCNN and ICM
- 5- Image Analysis
- 6- Feedback and Isolation
- 7- Recognition and Classification
- 8- Texture Recognition
- 9- Color and Multiple Channels
- 10- Image Signatures
- 11- Logic.
"Image Processing using Pulse-Coupled Neural Networks" Description:
The Open Library:
Image processing algorithms based on the mammalian visual cortex are powerful tools for extraction information and manipulating images. This book reviews the neural theory and translates them into digital models. Applications are given in areas of image recognition, foveation, image fusion and information extraction. The third edition reflects renewed international interest in pulse image processing with updated sections presenting several newly developed applications. This edition also introduces a suite of Python scripts that assist readers in replicating results presented in the text and to further develop their own applications.
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