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WSGAN: An Improved Generative Adversarial Network for Remote Sensing Image Road Network Extraction by Weakly Supervised Processing
2021
Remote Sensing
Road networks play an important role in navigation and city planning. However, current methods mainly adopt the supervised strategy that needs paired remote sensing images and segmentation images. These data requirements are difficult to achieve. The pair segmentation images are not easy to prepare. Thus, to alleviate the burden of acquiring large quantities of training images, this study designed an improved generative adversarial network to extract road networks through a weakly supervised
doi:10.3390/rs13132506
fatcat:dicf6ahhdrfcvgbtn4ma26q4tu