Rainfall cloud segmentation method in Tibet based on DeepLab v3
ZHANG Yonghong1,2, LIU Hao2, TIAN Wei3, WANG Jiangeng4
1. Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing Jiangsu 210044, China; 2. School of Automation, Nanjing University of Information Science and Technology, Nanjing Jiangsu 210044, China; 3. School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing Jiangsu 210044, China; 4. School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing Jiangsu 210044, China
Abstract：Concerning the problem that the numerical prediction method is complex in modeling, the radar echo extrapolation method is easy to generate cumulative error and the model parameters are difficult to set in plateau area, a method for segmenting rainfall clouds in Tibet was proposed based on the improved DeepLab v3. Firstly, the convolutional layers and residual modules in the coding network were used for down-sampling. Then, the multi-scale sampling module was constructed by using the dilated convolution, and the attention mechanism module was added to extract deep high-dimensional features. Finally, the deonvolutional layers in the decoding network were used to restore the feature map resolution. The proposed method was compared with Google semantic segmentation network DeepLab v3 and other models on the validation set. The experimental results show that the method has better segmentation performance and generalization ability, has the rainfall cloud segmented more accurately, and the Mean intersection over union (Miou) reached 0.95, which is 15.54 percentage points higher than that of the original DeepLab v3. On small targets and unbalanced datasets, rainfall clouds can be segmented more accurately by this method, so that the proposed method can provide a reference for the rain cloud monitoring and early warning.
张永宏, 刘昊, 田伟, 王剑庚. 基于DeepLab v3的西藏地区降雨云团分割方法[J]. 计算机应用, 2020, 40(9): 2781-2788.
ZHANG Yonghong, LIU Hao, TIAN Wei, WANG Jiangeng. Rainfall cloud segmentation method in Tibet based on DeepLab v3. Journal of Computer Applications, 2020, 40(9): 2781-2788.
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2020, Vol. 40 
