摘要
It has been shown that query can be correlated with its context to a different extent; in this case the feedback images. We introduce an adaptive weighting scheme where the respective weights are automatically modified, depending on the relationship strength between visual query and its visual context and textual query and its textual context; the number of terms or visual terms (mid-level visual features) co-occurring between current query and its context. The user simulation experiment has shown that this kind of adaptation can indeed further improve the effectiveness of hybrid CBIR models.
| 源语言 | 英语 |
|---|---|
| 主期刊名 | 2015 18th International Conference on Information Fusion, Fusion 2015 |
| 出版商 | Institute of Electrical and Electronics Engineers Inc. |
| 页 | 1322-1329 |
| 页数 | 8 |
| ISBN（电子版） | 9780982443866 |
| 出版状态 | 已出版 - 14 9月 2015 |
| 已对外发布 | 是 |
| 活动 | 18th International Conference on Information Fusion, Fusion 2015 - Washington, 美国 期限: 6 7月 2015 → 9 7月 2015 |
出版系列
| 姓名 | 2015 18th International Conference on Information Fusion, Fusion 2015 |
|---|
会议
| 会议 | 18th International Conference on Information Fusion, Fusion 2015 |
|---|---|
| 国家/地区 | 美国 |
| 市 | Washington |
| 时期 | 6/07/15 → 9/07/15 |
指纹
探究 'Adaptive relevance feedback for fusion of text and visual features' 的科研主题。它们共同构成独一无二的指纹。引用此
Kaliciak, L., Myrhaug, H., Goker, A., & Song, D. (2015). Adaptive relevance feedback for fusion of text and visual features. 在 2015 18th International Conference on Information Fusion, Fusion 2015 (页码 1322-1329). 文章 7266710 (2015 18th International Conference on Information Fusion, Fusion 2015). Institute of Electrical and Electronics Engineers Inc..