NCBI PubMed Central
open access
Deep learning and IoT-based framework for sesame plant identification and weed detection.
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
- Q-TriLSTM-Vision: a quantum-interference- augmented tri-stream LSTM for multi-label plant stress recognition on the OLID-I benchmark.#457530
- An intelligent SCADA-integrated deep learning framework for bird-safe offshore wind farm operation.#280908
- Polycyclic aromatic compounds in gull and tern eggs from breeding sites downstream of Athabasca oil sands mines (Alberta, Canada).#263335
- Leaf Nutrient Retrieval Using Hyperspectral Sensing and Machine Learning#202794
- Detection of tobacco seedlings in plastic-mulched fields using vegetation indices and YOLOv11.#1068861
Record · ID 381023
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