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Author  |
Albert Gordo; Florent Perronnin; Ernest Valveny | ||||
| Title | Document classification using multiple views | Type | Conference Article | ||
| Year | 2012 | Publication | 10th IAPR International Workshop on Document Analysis Systems | Abbreviated Journal | |
| Volume | Issue | Pages | 33-37 | ||
| Keywords | |||||
| Abstract | The combination of multiple features or views when representing documents or other kinds of objects usually leads to improved results in classification (and retrieval) tasks. Most systems assume that those views will be available both at training and test time. However, some views may be too `expensive' to be available at test time. In this paper, we consider the use of Canonical Correlation Analysis to leverage `expensive' views that are available only at training time. Experimental results show that this information may significantly improve the results in a classification task. | ||||
| Address | Australia | ||||
| Corporate Author | Thesis | ||||
| Publisher | IEEE Computer Society Washington | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-0-7695-4661-2 | Medium | ||
| Area | Expedition | Conference | DAS | ||
| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ GPV2012 | Serial | 2049 | ||
| Permanent link to this record | |||||