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A Feature Vector Approach for Inter-Query Learning for Content-Based Image Retrieval
2007
Journal of Advanced Computational Intelligence and Intelligent Informatics
Use of relevance feedback (RF) in the feature vector model has been one of the most widely used approaches to fine tuning queries for content-based image retrieval (CBIR). We propose a framework that extends RF to capturing the inter-query relationship between current and previous queries. Using the feature vector model, this avoids the need to "memorize" actual retrieval relationships between actual image indexes and the previous queries. This approach is suited to image database applications
doi:10.20965/jaciii.2007.p0289
fatcat:uerj5mrvyne33fdqu53tmo5auq