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- Publisher: Information Science Reference
- Year: 2012
- Pages: 424
- ISBN-10: 1466625392
- ISBN-13: 9781466625396
- Format: 21.8 x 28.2 x 3.1 cm, kieti viršeliai
- Language: English
- SAVE -10% with code: EXTRA
Developing and Applying Biologically-Inspired Vision Systems (e-book) (used book) | bookbook.eu
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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.
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- Publisher: Information Science Reference
- Year: 2012
- Pages: 424
- ISBN-10: 1466625392
- ISBN-13: 9781466625396
- Format: 21.8 x 28.2 x 3.1 cm, kieti viršeliai
- Language: English 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.
Reviews