Robust Cultivated Land Extraction Using Encoder-Decoder

作     者：Aziguli Wulamu Jingyue Sang Dezheng Zhang and Zuxian Shi 

作者机构：Department of ComputerSchool of Computer and Communication EngineeringUniversity of Science and Technology Beijing(USTB)Beijing100083China Beijing Key Laboratory of Knowledge Engineering for Materials ScienceBeijing100083China 不详 

出 版 物：《Journal of New Media》 (新媒体杂志（英文）)

年 卷 期：2020年第2卷第4期

页      面：149-155页

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：support for this work are as follows:Ningxia Hui Autonomous Region Key Research and Development Program Project:Research and demonstration application of key technologies for intelligent monitoring of spatial planning based on high-scoring remote sensing(Project No.2018YBZD1629) 

主　　题：Semantic segmentation encoder-decoder cultivated land extraction atrous convolution 

摘      要：Cultivated land extraction is essential for sustainable development and *** this paper,the network we propose is based on the encoder-decoder structure,which extracts the semantic segmentation neural network of cultivated land from satellite images and uses it for agricultural automation *** encoder consists of two part:the first is the modified Xception,it can used as the feature extraction network,and the second is the atrous convolution,it can used to expand the receptive field and the context information to extract richer feature *** decoder part uses the conventional upsampling operation to restore the original *** addition,we use the combination of BCE and Loves-hinge as a loss function to optimize the Intersection over Union(IoU).Experimental results show that the proposed network structure can solve the problem of cultivated land extraction in Yinchuan City.