A web-based platform for remote sensing image annotation
Keywords: Image annotation, object-based, active learning
Abstract
The generation of labeled data for training automated methods used in the analysis of remote sensing images is a challenging task. Approaches as Active Learning aim to perform accurate classifications in a scenario of a few annotated data. These approaches generally require the interaction between the user and the machine learning method during training phase. However, in the remote sensing area, it is difficult to find a tool that facilitates this interaction. In this work, an interactive web-based platform to perform the training of method for remote sensing image annotation by means of an active learning approach is proposed. The platform integrates open-source GIS technologies and object-based approach in order to facilitate the interaction between the user and the active learning approach. While some usability aspects should be improved, the obtained results show the potential of the proposed platform.
Más información
Fecha de publicación: | 2016 |
Idioma: | English |