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Performances of mobile-agents for interactive image retrieval

Abstract : In this paper, we present a system for image retrieval over a network of computer based on “ant-like” mobile- agents. Image databases are hosted on the network, and the user wants to find all the images matching a specific con- cept (cars, flower, Italy, etc...). Usually, content based im- age retrieval systems (CBIR) do not consider the dispertion of the data among the network. We train a SVM classifier with examples annotated by the user and then launch mobile agents which explore the network in order to retrieve the most relevant images. Several interactive session (launch- ing of agents then annotation of the results) are made to improve the classifier. Experiments are made both to see the influence of local- ization of the search concept on the quality of the learning, and to focus on the quality of the agent based solution com- pared to a centralizing system within a fixed amount of time for the interaction.
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Contributor : Arnaud Revel <>
Submitted on : Thursday, January 21, 2010 - 11:01:52 AM
Last modification on : Monday, January 25, 2021 - 3:16:03 PM



David Picard, Arnaud Revel, Matthieu Cord. Performances of mobile-agents for interactive image retrieval. Web Intelligence Conference, Dec 2006, Hong Kong, Hong Kong SAR China. pp.581-586, ⟨10.1109/WI.2006.129⟩. ⟨hal-00449294⟩



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