| Presentation | 1998/10/24 Learning of View-Invariant Pattern Recognizer with Temporal Context Kohei INOUE, Kiichi URAHAMA, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | RBF neural networks have been used for recognition of 3-dimensional objects view-invariantly on the basis of combination of some prototypical two-dimensional views of objects. In this paper, a feedback path is added to RBF nets for utilizing class-membership outputs at the previous time as a prior informarion at the current time. The network is trained unsupervisedly with the input of time-variant view images of some objects for developing view-invariant recognition capability. Robustification of data distribution enables the network to reject outlier data and to extract an object expected from the recognition at previous times. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | object recognition / RBF networks / membership feedback / roubst distribution |
| Paper # | NC98-43 |
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| Conference Information | |
| Committee | NC |
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| Conference Date | 1998/10/24(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
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| Paper Information | |
| 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) | Learning of View-Invariant Pattern Recognizer with Temporal Context |
| Sub Title (in English) | |
| Keyword(1) | object recognition |
| Keyword(2) | RBF networks |
| Keyword(3) | membership feedback |
| Keyword(4) | roubst distribution |
| 1st Author's Name | Kohei INOUE |
| 1st Author's Affiliation | Faculty of Visual Communication Design, Kyushu Institute of Design() |
| 2nd Author's Name | Kiichi URAHAMA |
| 2nd Author's Affiliation | Faculty of Visual Communication Design, Kyushu Institute of Design |
| Date | 1998/10/24 |
| Paper # | NC98-43 |
| Volume (vol) | vol.98 |
| Number (no) | 365 |
| Page | pp.pp.- |
| #Pages | 8 |
| Date of Issue | |