BMC@MediaEval 2017 multimedia satellite task via regression random forest

Publication Type:
Conference Proceeding
Citation:
CEUR Workshop Proceedings, 2017, 1984
Issue Date:
2017-01-01
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© 2017 Author/owner(s). In the MediaEval 2017 Multimedia Satellite Task, we propose an approach based on regression random forest which can extract valuable information from a few images and their corresponding metadata. The experimental results show that when processing social media images, the proposed method can be high-performance in circumstances where the images features are low-level and the training samples are relatively small of number.Additionally,when the low-level color features of satellite images are too ambiguous to analyze, random forest is also a efiective way to detect flooding area.
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