Developing and Applying Biologically-Inspired Vision Systems
Interdisciplinary Concepts
Nonfiction, Computers, Advanced Computing, Engineering, Computer Vision, Artificial Intelligence, General Computing
| Author: | ISBN: | 9781466625730 | |
| Publisher: | IGI Global | Publication: | November 30, 2012 |
| Imprint: | Information Science Reference | Language: | English |
| Author: | |
| ISBN: | 9781466625730 |
| Publisher: | IGI Global |
| Publication: | November 30, 2012 |
| Imprint: | Information Science Reference |
| Language: | English |
When comparing machine vision systems to the visual systems of humans and animals, there is much to be learned in terms of object segmentation, lighting invariance, and recognition of object categories. Studying the biological systems and applying the findings to the structure of computational vision models and artificial vision systems aims to be an essential approach of advancing the field of machine vision. Developing and Applying Biologically-Inspired Vision Systems: Interdisciplinary Concepts provides interdisciplinary research which evaluates the performance of machine visual models and systems in comparison to biological systems. Blending the ideas of current scientific knowledge and biological vision, this collection of new ideas intends to inspire approaches and cross-disciplinary research to applications in machine vision.
When comparing machine vision systems to the visual systems of humans and animals, there is much to be learned in terms of object segmentation, lighting invariance, and recognition of object categories. Studying the biological systems and applying the findings to the structure of computational vision models and artificial vision systems aims to be an essential approach of advancing the field of machine vision. Developing and Applying Biologically-Inspired Vision Systems: Interdisciplinary Concepts provides interdisciplinary research which evaluates the performance of machine visual models and systems in comparison to biological systems. Blending the ideas of current scientific knowledge and biological vision, this collection of new ideas intends to inspire approaches and cross-disciplinary research to applications in machine vision.
