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Found 7 papers, 2 papers with code
A CNN regression model to estimate buildings height maps using Sentinel-1 SAR and Sentinel-2 MSI time series
Accurate estimation of building heights is essential for urban planning, infrastructure management, and environmental analysis.
Context-Aware Change Detection With Semi-Supervised Learning
Change detection using earth observation data plays a vital role in quantifying the impact of disasters in affected areas.
Unsupervised Flood Detection on SAR Time Series
Our proposed CD model is evaluated on flood detection data.
Building Change Detection using Multi-Temporal Airborne LiDAR Data
For the change detection task, we used multi-temporal airborne LiDAR data.
Attentive Dual Stream Siamese U-net for Flood Detection on Multi-temporal Sentinel-1 Data
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.
Radar+RGB Attentive Fusion for Robust Object Detection in Autonomous Vehicles
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
Light-Weighted CNN for Text Classification
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
