论文标题
基于人工智能的人工智能技术为OpenStreetMap创建自然功能
Human Assisted Artificial Intelligence Based Technique to Create Natural Features for OpenStreetMap
论文作者
论文摘要
在这项工作中，我们建议使用诸如Landsat和Sentinel之类的自由卫星图像的基于AI的技术，以与OSM上的自然功能与人类编辑的一致性创建自然功能，该功能是发起人和验证者的。该方法基于交互式机器学习技术，其中人的输入与机器相结合，以有效地解决复杂问题，这与纯自主过程相比。我们使用一种自下而上的方法，其中机器学习（ML）管道在循环中使用编辑器用于使用图像的光谱签名提取类，然后将其转换为可编辑的功能以创建自然功能。
In this work, we propose an AI-based technique using freely available satellite images like Landsat and Sentinel to create natural features over OSM in congruence with human editors acting as initiators and validators. The method is based on Interactive Machine Learning technique where human inputs are coupled with the machine to solve complex problems efficiently as compare to pure autonomous process. We use a bottom-up approach where a machine learning (ML) pipeline in loop with editors is used to extract classes using spectral signatures of images and later convert them to editable features to create natural features.
