Synthetic Vision : : Using Volume Learning and Visual DNA / / Scott Krig.
In Synthetic Vision: Using Volume Learning and Visual DNA, a holistic model of the human visual system is developed into a working model in C++, informed by the latest neuroscience, DNN, and computer vision research. The author’s synthetic visual pathway model includes the eye, LGN, visual cortex, a...
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Superior document: | Title is part of eBook package: De Gruyter DG Plus DeG Package 2018 Part 1 |
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Place / Publishing House: | Boston ;, Berlin : : De|G Press, , [2018] ©2018 |
Year of Publication: | 2018 |
Language: | English |
Online Access: | |
Physical Description: | 1 online resource (XVIII, 350 p.) |
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100 | 1 | |a Krig, Scott, |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
245 | 1 | 0 | |a Synthetic Vision : |b Using Volume Learning and Visual DNA / |c Scott Krig. |
264 | 1 | |a Boston ; |a Berlin : |b De|G Press, |c [2018] | |
264 | 4 | |c ©2018 | |
300 | |a 1 online resource (XVIII, 350 p.) | ||
336 | |a text |b txt |2 rdacontent | ||
337 | |a computer |b c |2 rdamedia | ||
338 | |a online resource |b cr |2 rdacarrier | ||
347 | |a text file |b PDF |2 rda | ||
505 | 0 | 0 | |t Frontmatter -- |t About De/G PRESS -- |t Acknowledgments -- |t Contents -- |t Preface -- |t Chapter 1: Synthetic Vision Using Volume Learning and Visual DNA -- |t Chapter 2: Eye/LGN Model -- |t Chapter 3: Memory Model and Visual Cortex -- |t Chapter 4: Learning and Reasoning Agents -- |t Chapter 5: VGM Platform Overview -- |t Chapter 6: Volume Projection Metrics -- |t Chapter 7: Color 2D Region Metrics -- |t Chapter 8: Shape Metrics -- |t Chapter 9: Texture Metrics -- |t Chapter 10: Region Glyph Metrics -- |t Chapter 11: Applications, Training, Results -- |t Chapter 12: Visual Genome Project -- |t Bibliography -- |t Index |
506 | 0 | |a restricted access |u http://purl.org/coar/access_right/c_16ec |f online access with authorization |2 star | |
520 | |a In Synthetic Vision: Using Volume Learning and Visual DNA, a holistic model of the human visual system is developed into a working model in C++, informed by the latest neuroscience, DNN, and computer vision research. The author’s synthetic visual pathway model includes the eye, LGN, visual cortex, and the high level PFC learning centers. The corresponding visual genome model (VGM), begun in 2014, is introduced herein as the basis for a visual genome project analogous to the Human Genome Project funded by the US government. The VGM introduces volume learning principles and Visual DNA (VDNA) taking a multivariate approach beyond deep neural networks. Volume learning is modeled as programmable learning and reasoning agents, providing rich methods for structured agent classification networks. Volume learning incorporates a massive volume of multivariate features in various data space projections, collected into strands of Visual DNA, analogous to human DNA genes. VGM lays a foundation for a visual genome project to sequence VDNA as visual genomes in a public database, using collaborative research to move synthetic vision science forward and enable new applications. Bibliographical references are provided to key neuroscience, computer vision, and deep learning research, which form the basis for the biologically plausible VGM model and the synthetic visual pathway. The book also includes graphical illustrations and C++ API reference materials to enable VGM application programming. Open source code licenses are available for engineers and scientists. Scott Krig founded Krig Research to provide some of the world's first vision and imaging systems worldwide for military, industry, government, and academic use. Krig has worked for major corporations and startups in the areas of machine learning, computer vision, imaging, graphics, robotics and automation, computer security and cryptography. He has authored international patents in the areas of computer architecture, communications, computer security, digital imaging, and computer vision, and studied at Stanford. Scott Krig is the author of the English/Chinese Springer book Computer Vision Metrics, Survey, Taxonomy and Analysis of Computer Vision, Visual Neuroscience, and Deep Learning, Textbook Edition, as well as other books, articles, and papers. | ||
530 | |a Issued also in print. | ||
538 | |a Mode of access: Internet via World Wide Web. | ||
546 | |a In English. | ||
588 | 0 | |a Description based on online resource; title from PDF title page (publisher's Web site, viewed 04. Okt 2022) | |
650 | 0 | |a Computer vision. | |
650 | 4 | |a Bildbearbeitung. | |
650 | 4 | |a Computervision. | |
650 | 4 | |a Sensoren. | |
650 | 4 | |a Visualisierung. | |
650 | 7 | |a COMPUTERS / Computer Vision & Pattern Recognition. |2 bisacsh | |
653 | |a Computer Imaging. | ||
653 | |a Computer Vision. | ||
653 | |a Image Processing. | ||
653 | |a Sensor. | ||
653 | |a Synthetic Vision. | ||
653 | |a Visualization. | ||
773 | 0 | 8 | |i Title is part of eBook package: |d De Gruyter |t DG Plus DeG Package 2018 Part 1 |z 9783110762488 |
773 | 0 | 8 | |i Title is part of eBook package: |d De Gruyter |t DG Plus eBook-Package 2018 |z 9783110719550 |
773 | 0 | 8 | |i Title is part of eBook package: |d De Gruyter |t EBOOK PACKAGE COMPLETE 2018 English |z 9783110604252 |
773 | 0 | 8 | |i Title is part of eBook package: |d De Gruyter |t EBOOK PACKAGE COMPLETE 2018 |z 9783110603255 |o ZDB-23-DGG |
773 | 0 | 8 | |i Title is part of eBook package: |d De Gruyter |t EBOOK PACKAGE Engineering, Computer Sciences 2018 English |z 9783110604023 |
773 | 0 | 8 | |i Title is part of eBook package: |d De Gruyter |t EBOOK PACKAGE Engineering, Computer Sciences 2018 |z 9783110603118 |o ZDB-23-DEI |
776 | 0 | |c EPUB |z 9781501506291 | |
776 | 0 | |c print |z 9781501515170 | |
856 | 4 | 0 | |u https://doi.org/10.1515/9781501505966 |
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856 | 4 | 2 | |3 Cover |u https://www.degruyter.com/document/cover/isbn/9781501505966/original |
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