| Abstract: | Attempts at fully automated object recognition systems have met with varying levels of success over the years. However, none of the systems have achieved high enough accuracy rates to be run unattended. One of the reasons for this may be that they are designed from the computer‘s point of view and rely mainly on image-processing methods. A better solution to this problem may be to make use of modern advances in computational intelligence and distributed processing to try to mimic how the human brain is thought to recognize objects. As humans combine cognitive processes with detection techniques, such a system would combine traditional image-processing techniques with computer-based intelligence to determine the identity of various objects in a scene. |
| Genre: | USGS Numbered Series |
| ProdID: | 50722 |
| Citation Author: | Maddox, Brian G.; Swadley, Casey L. |
| Citation Contributing Office: | Geological Survey (U.S.) |
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| Citation Language: | ENGLISH |
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| Citation Phsyical Description: | 15 p. |
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| Citation Publisher: | Geological Survey (U.S.) |
| Citation Series: | Open-File Report |
| Citation Series Code: | OFR |
| Citation Series Number: | 2002-461 |
| Citation Search Results Text: | An Intelligent Systems Approach to Automated Object Recognition: A Preliminary Study; 2002; OFR; 2002-461; Maddox, Brian G.; Swadley, Casey L. |
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| Citation Year: | 2002 |
| Type: | citation/reference |
| Text: | An Intelligent Systems Approach to Automated Object Recognition: A Preliminary Study; 2002; OFR; 2002-461; Maddox, Brian G.; Swadley, Casey L. |
| URL (THUMBNAIL): | http://pubs.er.usgs.gov/thumbnails/usgs_thumb.jpg |
| URL (INDEX PAGE): | http://pubs.usgs.gov/of/2002/0461/ |
| Date Other: | Sat, 1 Jan 1994 00:00 -0600 |
| Publisher: | Geological Survey (U.S.) |