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Found 8 papers, 5 papers with code
Bringing SAM to new heights: Leveraging elevation data for tree crown segmentation from drone imagery
We present BalSAM, a model leveraging SAM and DSM information, which shows potential over other methods, particularly in the context of plantations.
Assessing SAM for Tree Crown Instance Segmentation from Drone Imagery
In this work, we compare SAM methods for the task of automatic tree crown instance segmentation in high resolution drone imagery of young tree plantations.
Tree semantic segmentation from aerial image time series
Earth's forests play an important role in the fight against climate change, and are in turn negatively affected by it.
FoMo-Bench: a multi-modal, multi-scale and multi-task Forest Monitoring Benchmark for remote sensing foundation models
Inspired by the rise of foundation models for computer vision and remote sensing, we here present the first unified Forest Monitoring Benchmark (FoMo-Bench).
OpenForest: A data catalogue for machine learning in forest monitoring
These datasets are grouped in OpenForest, a dynamic catalogue open to contributions that strives to reference all available open access forest datasets.
Deep learning for radar data exploitation of autonomous vehicle
It will also describe the CARRADA dataset, composed of synchronised camera and RADAR data with a semi-automatic annotation method.
Raw High-Definition Radar for Multi-Task Learning
With their robustness to adverse weather conditions and ability to measure speeds, radar sensors have been part of the automotive landscape for more than two decades.
Multi-View Radar Semantic Segmentation
Understanding the scene around the ego-vehicle is key to assisted and autonomous driving.
