| Presentation | 1998/3/20 A Visual Nervous System based Multi-Module Neural Network for Object Recognition Tetsuya TNNAI, Masafumi HAGIWARA, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | When we recognize a object, unite the part features, and recognize whole object. We propose a multi-module neural network model based on information processing of the visual nervous system. In this paper, we constract the system that extract a human face area from image with background. This system consists of several modules that is learned to respond selectively to human face component, eyes, nose, and mouth. At last extract face area where the outputs of previous cell layer is located correctly to human face component. We carried out a lot of experiments using 100 images having complex background to examine the effectiveness of the proposed scheme. 83% of faces are detected correctly. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Visual Nervous System / Multi-Module / Neocognitron / Part Feature / Face Extraction |
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| Conference Information | |
| Committee | NC |
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| Conference Date | 1998/3/20(1days) |
| Place (in Japanese) | (See Japanese page) |
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| Topics (in Japanese) | (See Japanese page) |
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| Registration To | Neurocomputing (NC) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A Visual Nervous System based Multi-Module Neural Network for Object Recognition |
| Sub Title (in English) | |
| Keyword(1) | Visual Nervous System |
| Keyword(2) | Multi-Module |
| Keyword(3) | Neocognitron |
| Keyword(4) | Part Feature |
| Keyword(5) | Face Extraction |
| 1st Author's Name | Tetsuya TNNAI |
| 1st Author's Affiliation | Department of Electrical Engineering, Faculty of Science and Technology, Keio University() |
| 2nd Author's Name | Masafumi HAGIWARA |
| 2nd Author's Affiliation | Department of Electrical Engineering, Faculty of Science and Technology, Keio University |
| Date | 1998/3/20 |
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| Volume (vol) | vol.97 |
| Number (no) | 624 |
| Page | pp.pp.- |
| #Pages | 8 |
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