arXiv (All)
open access
HSI-Road Relabeled: Surface-Aware Road-Scene Segmentation
The HSI-Road dataset provides paired RGB and 25-channel NIR (600--960~nm) images with binary masks but no surface-level labels.~This paper introduces a manually labeled six-class taxonomy: Background, Asphalt, Concrete, Dirt, Water, and Grass, and an RGB-to-NIR registration pipeline with correspondi
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- SegCol Challenge: Semantic Segmentation for Tools and Fold Edges in Colonoscopy data#1122903
- HydroMap: Probabilistic Water Surface Elevation Mapping for Semantic Scene Representation in Inland Waterways#1149478
- Contextual Semantic Mapping Dataset for Intralogistics: RGB Images, 2D LiDAR Scans, and SAM Instance Annotations#309497
- Weather-Aware Domain Adaptation for Street-View Weather Recognition#1161049
- Weather-Aware Domain Adaptation for Street-View Weather Recognition#1157348
Record · ID 1000117
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive