Ground-based Detection of Martian Dust Devils With a Fine-tuned Fast R-CNN

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We developed a two-stage pipeline for efficient dust devil detection in Mars rover imagery. Our approach combines preprocessing filters to remove unsuitable images, followed by a Faster R-CNN with ResNet-50 backbone and Feature Pyramid Network, effectively detecting nonrigid, low-opacity dust devils that traditional methods frequently miss. We demonstrated clear advantages over generic object detection models.