Accurate estimation of building heights is essential for urban planning, infrastructure management, and environmental analysis.
The experiments highlight that the combination of bi-temporal SAR data with an effective network architecture achieves more accurate flood detection than uni-temporal methods.
BIRANet yields 72. 3/75. 3% average AP/AR on the NuScenes dataset, which is better than the performance of our base network Faster-RCNN with Feature pyramid network(FFPN).
Ranked #1 on Object Detection on nuScenes
As a solution to this problem, we introduced a whole new architecture based on separable convolution.
Ranked #1 on Document Text Classification on Tobacco-3482