AI RESEARCH
BAWSeg: A UAV Multispectral Benchmark for Barley Weed Segmentation
arXiv CS.CV
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ArXi:2603.01932v2 Announce Type: replace Accurate weed mapping in cereal fields requires pixel-level segmentation from UAV imagery that remains reliable across fields, seasons, and illumination. Existing multispectral pipelines often depend on thresholded vegetation indices, which are brittle under radiometric drift and mixed crop--weed pixels, or on single-stream CNN and Transformer backbones that ingest stacked bands and indices, where radiance cues and normalized index cues interfere and reduce sensitivity to small weed clusters embedded in crop canopy.