NCBI PubMed Central
open access
Non-destructive yield estimation of onion and garlic using UAV-based hyperspectral imaging and hybrid machine learning models.
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
- Food Origin Authenticity Using Deep Learning and Citizen Science#218190
- Deep learning for sorghum yield forecasting using uncrewed aerial systems and lab-derived imagery.#138451
- Machine Learning para detectar enfermedades tempranas en plantaciones de café en el departamento de Amazonas, 2025#276445
- Influence of a garlic-based additive on the performance parameters and intestinal morphology of replacement gilts in Ukraine under commercial conditions.#135918
- PlantC2USeg: Cross-Scale Consistent Pre-Training for Few-Shot Unified Plant Point Cloud Segmentation#924978
Record · ID 305113
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