This code is for our paper "Transferred deep learning for sea ice change detection from synthetic aperture radar images". If you use this code, please kindly cite our paper: Yunhao Gao, Feng Gao*, Junyu Dong, Shenke Wang. "Transferred deep learning for sea ice change detection from synthetic aperture radar Images". IEEE Geoscience and Remote Sensing Letters, vol. 16, no.10, pp. 1655-1659, Oct. 2019.

If you have any questions, please contact us. Email: gaoyunhao128@163.com gaofeng@ouc.edu.cn

Before running this code, you should correctly install ubuntu system and caffe framework. Refer to this guildeline "http://caffe.berkeleyvision.org/installation.html" After correctly installing ubuntu and caffe, you can run this code by the following procedures.

(1) Opening the Matlab and changing the current path, running the "generating_train.m" and "generating_test.m" to generate the training and testing samples

(2) Running the "create_train.sh" and "create_test.sh" in Caffe. Therefore, the format "png" can be converted to format "lmdb" which is efficent for the caffe input

(3) Opening the terminal and running this script to execute the training of MLFN: "sh train.sh"

(4) After training, running the following script to executes the testing of MLFN and record testing logs: "sh test.sh >& info/result.txt"

(5) Running the "extract_prob.sh" in Caffe to extract probability from the "result.txt"

(6) Running the "calculating_result.m" in Matlab to calculate the matrics (PCC, Kappa, FP and FN) and draw the final change map.