BAWSeg: A UAV Multispectral Benchmark for Barley Weed Segmentation
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. We propose VISA, a two-stream segmentation network that decouples these cues and fuses them at native resolution. The radiance stream learns from calibrated five-band reflecta...
| Authors | Haitian Wang, Xinyu Wang, Muhammad Ibrahim et al. |
|---|---|
| Primary category | cs.CV |
| Published | 2 March 2026 |
| Last updated at source | 17 March 2026 |
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