| Presentation | 2013/9/5 Fish Detection by LBP Cascade Classifier with Optimized Processing Pipeline HOANGANH DANG, PAO SRIPRASERTSUK, WATARU KAMEYAMA, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In this paper, we present a fish detection and classification mechanism using LBP feature. In this system, training sets are created for each fish species. Besides the strict sample alignment, a processing pipeline is applied in both training and detection process to achieve high performance of detection task. This pipeline further highlights unique features of each species such as edges and dominant colors. Machine learning is used to find the best pipeline model to be applied for each training set. A case study at a local aquarium shows high accuracy at a compelling detection rate. |
| Keyword(in Japanese) | (See Japanese page) |
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| Paper # | Vol.2013-AVM-82 NO.9 |
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| Conference Information | |
| Committee | SIS |
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| Conference Date | 2013/9/5(1days) |
| Place (in Japanese) | (See Japanese page) |
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| Topics (in Japanese) | (See Japanese page) |
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| Registration To | Smart Info-Media Systems (SIS) |
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| Language | ENG |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Fish Detection by LBP Cascade Classifier with Optimized Processing Pipeline |
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| 1st Author's Name | HOANGANH DANG |
| 1st Author's Affiliation | () |
| 2nd Author's Name | PAO SRIPRASERTSUK |
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| 3rd Author's Name | WATARU KAMEYAMA |
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| Date | 2013/9/5 |
| Paper # | Vol.2013-AVM-82 NO.9 |
| Volume (vol) | vol.113 |
| Number (no) | 202 |
| Page | pp.pp.- |
| #Pages | 4 |
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