@inproceedings{7c8ca79052ba4d16af477cc30b2afdfa,
title = "Bounding Box Regression Network for Building Height Retrieval Using a Single SAR Image",
abstract = "In this paper, we propose a bounding box regression network for building height retrieval using a single TerraSAR-X stripmap image. The proposed network employs building footprints from GIS data and exploits the location relationship between a building's footprint and its bounding box, enabling fast computation. Experimental results over Rotterdam show that the proposed network can reduce the computation cost significantly while keeping the height accuracy of individual buildings compared to a Faster R-CNN based method.",
keywords = "GIS, bounding box, building height, deep convolutional neural network (CNN), large-scale, synthetic aperture radar (SAR)",
author = "Yao Sun and Lichao Mou and Yuanyuan Wang and Zhu, \{Xiao Xiang\}",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022 ; Conference date: 17-07-2022 Through 22-07-2022",
year = "2022",
doi = "10.1109/IGARSS46834.2022.9884836",
language = "English",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "56--59",
booktitle = "IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium",
}