| Vorliegende Sprache |
eng |
| Hinweise auf parallele Ausgaben |
386793662 Druckausg.: ‡Lindblad, Thomas, 1945 - : Image processing using pulse-coupled neural networks |
| ISBN |
978-3-642-36876-9 |
| Name |
Lindblad, Thomas |
| Kinser, Jason M. |
| ANZEIGE DER KETTE |
Kinser, Jason M. |
| T I T E L |
Image Processing using Pulse-Coupled Neural Networks |
| Zusatz zum Titel |
Applications in Python |
| Auflage |
3rd ed. 2013 |
| Verlagsort |
Berlin, Heidelberg |
| Verlag |
Springer |
| Erscheinungsjahr |
2013 |
| 2013 |
| Umfang |
Online-Ressource (XXIV, 238 p. 142 illus., 9 illus. in color, digital) |
| Reihe |
Biological and Medical Physics, Biomedical Engineering |
| Notiz / Fußnoten |
Includes bibliographical references and index |
| Weiterer Inhalt |
Preface to the Third Edition; Preface to the Second Edition; Preface to the First Edition; Contents; 1 Biological Models; 1.1 Introduction; 1.2 Biological Foundation; 1.3 Hodgkin-Huxley; 1.4 Fitzhugh-Nagumo; 1.5 Eckhorn Model; 1.6 Rybak Model; 1.7 Parodi Model; 1.8 Summary; 2 Programming in Python; 2.1 Environment; 2.1.1 Command Interface; 2.1.2 IDLE; 2.1.3 Establishing a Working Environment; 2.2 Data Types and Simple Math; 2.3 Tuples, Lists, and Dictionaries; 2.3.1 Tuples; 2.3.2 Lists; 2.3.3 Dictionaries; 2.4 Slicing; 2.5 Strings; 2.5.1 String Functions; 2.5.2 Type Casting; 2.6 Control. 2.7 Input and Output2.7.1 Basic Files; 2.7.2 Pickle; 2.8 Functions; 2.9 Modules; 2.10 Object Oriented Programming; 2.10.1 Content of a Class; 2.10.2 Operator Definitions; 2.10.3 Inheritance; 2.11 Error Checking; 2.12 Summary; 3 NumPy, SciPy and Python Image Library; 3.1 NumPy; 3.1.1 Creating Arrays; 3.1.2 Converting Arrays; 3.1.3 Matrix: Vector Multiplications; 3.1.4 Justification for Arrays; 3.1.5 Data Types; 3.1.6 Sorting; 3.1.7 Conversions to Strings and Lists; 3.1.8 Changing the Matrix; 3.1.9 Advanced Slicing; 3.2 SciPy; 3.3 Designing in Numpy; 3.4 Python Image Library. 3.4.1 Reading an Image3.4.2 Writing an Image; 3.4.3 Transforming an Image; 3.5 Summary; 4 The PCNN and ICM; 4.1 The PCNN; 4.1.1 Original Model; 4.1.2 Implementing in Python; 4.1.3 Spiking Behaviour; 4.1.4 Collective Behaviour; 4.1.5 Time Signatures; 4.1.6 Neural Connections; 4.1.7 Fast Linking; 4.1.8 Models in Analogue Time; 4.2 The ICM; 4.2.1 Minimum Requirements; 4.2.2 ICM Theory; 4.2.3 Connections in the ICM; 4.2.4 Python Implementation; 4.3 Summary; 5 Image Analysis; 5.1 Pertinent Image Information; 5.2 Image Segmentation; 5.2.1 Blood Cells; 5.2.2 Mammography; 5.3 Adaptive Segmentation. 5.4 Focus and Foveation5.4.1 The Foveation Algorithm; 5.4.2 Target Recognition by a PCNN-Based Foveation Model; 5.5 Image Factorisation; 5.6 Summary; 6 Feedback and Isolation; 6.1 A Feedback PCNN; 6.2 Object Isolation; 6.2.1 Input Normalisation; 6.2.2 Creating the Filter; 6.2.3 Edge Enhancement of Pulse Images; 6.2.4 Correlation and Modifications; 6.2.5 Peak Detection; 6.2.6 Modifications to the Input and PCNN; 6.2.7 Drivers; 6.3 Dynamic Object Isolation; 6.4 Shadowed Objects; 6.5 Consideration of Noisy Images; 6.6 Summary; 7 Recognition and Classification; 7.1 Aircraft; 7.2 Aurora Borealis. 7.3 Target Identification: Binary Correlations7.4 Galaxies; 7.5 Hand Gestures; 7.6 Road Surface Inspection; 7.7 Numerals; 7.7.1 Data Set; 7.7.2 Isolating a Class for Training; 7.8 Generating Pulse Images; 7.8.1 Analysis of the Signatures; 7.9 Face Location and Identification; 7.10 Summary; 8 Texture Recognition; 8.1 Pulse Spectra; 8.2 Statistical Separation of the Spectra; 8.3 Recognition Using Statistical Methods; 8.4 Recognition of the Pulse Spectra via an Associative Memory; 8.5 Biological Application; 8.6 Texture Study; 8.7 Summary; 9 Colour and Multiple Channels; 9.1 The Model. 9.1.1 Colour Example |
| Titelhinweis |
Druckausg.: ‡Lindblad, Thomas, 1945 - : Image processing using pulse-coupled neural networks |
| ISBN |
ISBN 978-3-642-36877-6 |
| Klassifikation |
TTBM |
| UYS |
| TEC008000 |
| COM073000 |
| *68U10 |
| 68T05 |
| 68-00 |
| 621.382 |
| 006.6 |
| TK5102.9 |
| TA1637-1638 |
| TK7882.S65 |
| Kurzbeschreibung |
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 |
| 1. Schlagwortkette |
Bildverarbeitung |
| Pulsverarbeitendes neuronales Netz |
| Python 2.7 |
| 1. Schlagwortkette ANZEIGE DER KETTE |
Bildverarbeitung -- Pulsverarbeitendes neuronales Netz -- Python 2.7 |
| 2. Schlagwortkette |
Bildverarbeitung |
| Pulsverarbeitendes neuronales Netz |
| Python <Programmiersprache> |
| ANZEIGE DER KETTE |
Bildverarbeitung -- Pulsverarbeitendes neuronales Netz -- Python |
| SWB-Titel-Idn |
383258464 |
| Signatur |
Springer E-Book |
| Bemerkungen |
Elektronischer Volltext - Campuslizenz |
| Elektronische Adresse |
$uhttp://dx.doi.org/10.1007/978-3-642-36877-6 |
| Internetseite / Link |
Volltext |
| Siehe auch |
Inhaltstext |
| Siehe auch |
Volltext |
| Siehe auch |
Cover |
| Siehe auch |
Inhaltstext |
