Optimizing Learning in Image Retrieval Export

@proceedings{citeulike:3524, abstract = {Combining learning with vision techniques in interactive image retrieval has been an active research topic during the past few years. However, existing learning techniques either are based on heuristics or fail to analyze the working conditions. Furthermore, there is almost no in depth study on how to effectively learn from the users when there are multiple visual features in the retrieval system. To address these limitations, in this paper, we present a vigorous optimization formulation of the ...}, author = {Rui, Y. and Huang, T.}, citeulike-article-id = {3524}, citeulike-linkout-0 = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.34.9446}, keywords = {cbir, rf}, pages = {236--245}, posted-at = {2004-12-13 15:20:35}, priority = {0}, title = {Optimizing Learning in Image Retrieval}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.34.9446} }

TY - CONF ID - citeulike:3524 L3 - citeulike-article-id:3524 N2 - Combining learning with vision techniques in interactive image retrieval has been an active research topic during the past few years. However, existing learning techniques either are based on heuristics or fail to analyze the working conditions. Furthermore, there is almost no in depth study on how to effectively learn from the users when there are multiple visual features in the retrieval system. To address these limitations, in this paper, we present a vigorous optimization formulation of the ... EP - 245 TI - Optimizing Learning in Image Retrieval SP - 236 KW - cbir KW - rf AU - Rui, Y AU - Huang, T UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.34.9446 ER -