4/21/2023 0 Comments Google earth aerial view![]() ![]() To overcome this challenge, we propose, in this manuscript, scale-invariant neural network (Sci-Net) architecture that segments buildings from wide-range spatial resolution aerial images. Thus, a given aerial image often needs to be re-sampled to match the spatial resolution of the dataset used to train the deep learning model, which results in a degradation in segmentation performance. In practical scenarios, users deal with a broad spectrum of image resolutions. Most existing deep learning-based methods in the literature can be applied to a fixed or narrow-range spatial resolution imagery. Buildings’ segmentation is a fundamental task in the field of earth observation and aerial imagery analysis.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |