Given a user's visual query, most visual information retrieval (VIR) systems rank the images in the database according to a predefined measure of similarity and return the most similar ones. We propose an adaptive VIR system that uses a retrieval process based on relevance feedback in order to learn the similarity criterion from the user. Our system is based on a structured representation of the image which is then processed by a recursive neural network. The search algorithm refines its response trying to minimize the number of steps required to find the target image.
DE MAURO, C., Gori, M., Maggini, M. (2001). APEX: an adaptive visual information retrieval system. In Proceedings of the Sixth International Conference on Document Analysis and Recognition (pp.898-902). IEEE [10.1109/ICDAR.2001.953916].
APEX: an adaptive visual information retrieval system
GORI M.;MAGGINI M.
2001-01-01
Abstract
Given a user's visual query, most visual information retrieval (VIR) systems rank the images in the database according to a predefined measure of similarity and return the most similar ones. We propose an adaptive VIR system that uses a retrieval process based on relevance feedback in order to learn the similarity criterion from the user. Our system is based on a structured representation of the image which is then processed by a recursive neural network. The search algorithm refines its response trying to minimize the number of steps required to find the target image.
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https://hdl.handle.net/11365/37659
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