arXiv (All)
open access
Robustness Verification of an Autonomous Underwater Vehicle-based Plankton Classifier
The assessment of planktonic standing stocks and microorganism structures is critical for understanding upper ocean biological processes. Currently, autonomous underwater vehicles (AUVs) equipped with in-situ optical imaging and artificial intelligence (AI) methods offer a promising solution for per
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
- Something looks fishy! A philosophical exploration of AI for marine conservation.#636602
- A Paired RGB-Sonar Dataset for Fish Monitoring with Consumer Sonar#1388131
- A GPU-Resident Pipeline for Multi-Robot 3D Inspection with Limited Perception#1401285
- IMAGE QUALITY ASSESSMENT OF ACTIVE SONAR IMAGES THROUGH BAYESIAN DEEP LEARNING#1258835
- Experimental Proof-of-Concept of Passive Bio-Inspired Sensing Strategy for Autonomous Underwater Vehicles#337736
Record · ID 1423914
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