Diversity-driven learning for multimodal image retrieval with relevance feedback

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@InProceedings{Calumby:2014:ICIP,

• author = "R. T. Calumby and R. {da Silva Torres} and M. A. Goncalves",
• booktitle = "IEEE International Conference on Image Processing (ICIP 2014)",
• title = "Diversity-driven learning for multimodal image retrieval with relevance feedback",
• year = "2014",
• month = oct,
• pages = "2197--2201",
• abstract = "We introduce a new genetic programming approach for enhancing the user search experience based on relevance feedback over results produced by a multimodal image retrieval technique with explicit diversity promotion. We have studied maximal marginal relevance re-ranking methods for result diversification and their impacts on the overall retrieval effectiveness. We show that the learning process using diverse results may improve user experience in terms of both the number of relevant items retrieved and subtopic coverage.",
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/ICIP.2014.7025445",
• notes = "Also known as \cite{7025445}",

}

Genetic Programming entries for Rodrigo Tripodi Calumby Ricardo da Silva Torres Marcos Andre Goncalves

Citations