论文标题
在卫星图像和后加工方法的性能上进行分割
Building Segmentation on Satellite Images and Performance of Post-Processing Methods
论文作者
论文摘要
由于其包含计算机视觉算法的开发以及卫星图像的可访问性，研究人员正在对卫星图像进行大量工作。卫星图像的构建细分可用于许多潜在应用，例如城市，农业和通信网络计划。但是，由于每个区域都不存在数据集，因此在区域中训练的模型必须获得一般性。在这项研究中，我们在中国培训了几种模型，并在其中选择的最佳模型进行了后处理工作。这些模型在Inria数据集的芝加哥地区进行了评估。从结果可以看出，尽管尚未实现该领域的最先进结果，但结果是有希望的。我们的目的是在本研究中介绍从卫星图像进行建筑物分割的最初实验结果。
Researchers are doing intensive work on satellite images due to the information it contains with the development of computer vision algorithms and the ease of accessibility to satellite images. Building segmentation of satellite images can be used for many potential applications such as city, agricultural, and communication network planning. However, since no dataset exists for every region, the model trained in a region must gain generality. In this study, we trained several models in China and post-processing work was done on the best model selected among them. These models are evaluated in the Chicago region of the INRIA dataset. As can be seen from the results, although state-of-art results in this area have not been achieved, the results are promising. We aim to present our initial experimental results of a building segmentation from satellite images in this study.
