BMC@MediaEval 2017 Multimedia Satellite Task via Regression Random Forest
نویسندگان
چکیده
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 e ective way to detect ooding area.
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