Most of the current image retrieval systems use "one-shot" queries to a database to retrieve similar images. Typically a Knearest neighbor kind of algorithm is used, where weights measuring feature importance along each input dimension remain fixed (or manually tweaked by the user), in the computati
โฆ LIBER โฆ
Region-based Image Retrieval Using Probabilistic Feature Relevance Learning
โ Scribed by ByoungChul Ko, Jing Peng, Hyeran Byun
- Book ID
- 113054519
- Publisher
- Springer-Verlag
- Year
- 2001
- Tongue
- English
- Weight
- 991 KB
- Volume
- 4
- Category
- Article
- ISSN
- 1433-7541
No coin nor oath required. For personal study only.
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Database search engines are generally used in a one-shot fashion in which a user provides query information to the system and, in return, the system provides a number of database instances to the user. A relevance feedback system allows the user to indicate to the system which of these instances are