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| Title: | Image recognition systems with permutative coding | |
| Author (s): | Kussul, E. Baidyk, T. Wunsch, Donald C. | |
| Department/Lab Affiliations: | Applied Computational Intelligence Laboratory Electrical and Computer Engineering | |
| Keywords: | MNIST database ORL database face recognition feature extraction feature extractor handwriting recognition handwritten digit recognition image coding image recognition image recognition system microobjects recognition neural classifier neural nets neural network object recognition permutative coding visual databases | |
| Issue Date: | 2005 | |
| Publisher: | Institute of Electrical and Electronics Engineers | |
| Citation: | Kussul, E.; Baidyk, T.; Wunsch, D.C., II, "Image recognition systems with permutative coding" IJCNN '05. Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005. pp. 1788- 1793 vol. 3, 31 July-4 Aug. 2005 | |
| Abstract: | A feature extractor and neural classifier for image recognition system are proposed. They are based on the permutative coding technique which continues our investigations on neural networks. It permits us to obtain sufficiently general description of the image to be recognized. Different types of images were used to test the proposed image recognition system. It was tested on the handwritten digit recognition problem, the face recognition problem and the shape of microobjects recognition problem. The results of testing are very promising. The error rate for the MNIST database is 0.44% and for the ORL database is 0.1%. | |
| Type: | Article - Conference proceedings text | |
| Copyright Notice: | This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. FULL COPYRIGHT INFORMATION: | |
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| title | Image recognition systems with permutative coding | |
| contributor.author | Kussul, E. | |
| contributor.author | Baidyk, T. | |
| contributor.author | Wunsch, Donald C. | |
| contributor.deptlab | Applied Computational Intelligence Laboratory | |
| contributor.deptlab | Electrical and Computer Engineering | |
| subject | MNIST database | |
| subject | ORL database | |
| subject | face recognition | |
| subject | feature extraction | |
| subject | feature extractor | |
| subject | handwriting recognition | |
| subject | handwritten digit recognition | |
| subject | image coding | |
| subject | image recognition | |
| subject | image recognition system | |
| subject | microobjects recognition | |
| subject | neural classifier | |
| subject | neural nets | |
| subject | neural network | |
| subject | object recognition | |
| subject | permutative coding | |
| subject | visual databases | |
| date.issued | 2005 | |
| date.submitted | 2007 | |
| publisher | Institute of Electrical and Electronics Engineers | |
| identifier.citation | Kussul, E.; Baidyk, T.; Wunsch, D.C., II, "Image recognition systems with permutative coding" IJCNN '05. Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005. pp. 1788- 1793 vol. 3, 31 July-4 Aug. 2005 | |
| identifier.pub.URI | ||
| description.abstract | A feature extractor and neural classifier for image recognition system are proposed. They are based on the permutative coding technique which continues our investigations on neural networks. It permits us to obtain sufficiently general description of the image to be recognized. Different types of images were used to test the proposed image recognition system. It was tested on the handwritten digit recognition problem, the face recognition problem and the shape of microobjects recognition problem. The results of testing are very promising. The error rate for the MNIST database is 0.44% and for the ORL database is 0.1%. | |
| type | Article - Conference proceedings | |
| type.DCMIType | text | |
| type.status | Final version | |
| rights | This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. | |
| rights.URI | ||
| date.accessioned | 2007-04-05T14:25:21Z | |
| date.available | 2007-04-05T14:25:20Z | |
| identifier.persist.URI | ||
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