Convolutional models like YOLOv11 and Mask R-CNN outperform transformer-based models for tree canopy segmentation when fine-tuned on just 150 images.
Very high resolution canopy height maps from rgb imagery using self-supervised vision transformer and convolutional decoder trained on aerial lidar,
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Sparse Data Tree Canopy Segmentation: Fine-Tuning Leading Pretrained Models on Only 150 Images
Convolutional models like YOLOv11 and Mask R-CNN outperform transformer-based models for tree canopy segmentation when fine-tuned on just 150 images.