BMC@MediaEval 2017 multimedia satellite task via regression random forest
Xiyao Fu, Yi Bin, Liang Peng, Jie Zhou, Yang Yang, Heng Tao Shen · UTS ePRESS (University of Technology Sydney) · 2017
© 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.