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Research on Adaptive Segmentation of Typical Objects in Remote Sensing Images

Research on Adaptive Segmentation of Typical Objects in Remo...

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第32届中国控制与决策会议

作者： Chang Wang Lei Zhu Wenwu Wang Bin Zhang Ganshui Zhou School of information science and engineering Wuhan University of science and technology WISDRI CCTEC Engineering Co. Ltd

The high-resolution remote sensing image contains rich information of surface ***,the same surface features collected in different regions at different times still have large appearance *** problem makes the network parameters trained in a single environment difficult to adapt to the extraction of similar objects in different *** order to solve these problems,this paper proposes a domain adaptive method based on CNN to solve the single class target segmentation problem in different feature domains for remote sensing *** model consists of two ***,this paper selects a segmentation framework suitable for remote sensing image feature extraction as a *** feature layers of the generator are extracted to describe the source domain and the target domain image in multiple ***,the features are used as the input of the discriminator to adversarial learning to distinguish whether the input is from the source image or the target *** order to verify the effectiveness of the algorithm,this paper takes the extraction of planting greenhouses in remote sensing images as an example,first this paper proposes a data set for the extraction of planting greenhouses and carries out pixel level ***,the remote sensing image of the greenhouse in Chenggong District,Kunming City,Yunnan Province,South China was made into the labeled source data,and the remote sensing image of the greenhouse in the Inner Mongolia Autonomous Region of the North was used as the target data of the *** experimental results on the database show that the recall rate and accuracy of the proposed algorithm are good,and the MAE is 0.544,which is better than the existing feature extraction method based on migration learning.

关键词： terrain segmentation adaptive learning in feature domain convolution neural network remote sensing image planting greenhouse average absolute error

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