HAL (France)
open access
Graph-based Moving Object Segmentation for underwater videos using semi-supervised learning
Moving object segmentation (MOS) using passive underwater image processing is an important technology for monitoring marine habitats. It aids marine biologists studying biological oceanography and the associated fields of chemical, physical, and geological oceanography to understand marine organisms
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
- Exploring the Underwater World Segmentation without Extra Training#1325058
- CoRef-DETR: Decoupled Global Context and Selective Boundary-Category Refinement for Underwater Instance Segmentation#1296438
- LoRA Enhanced Contrastive Learning with SAS Vision Transformers#1035031
- CoralPlan: Observation Skill Selection and Execution for Underwater Robotic Inspection#1105769
- Towards Scaling Marine Perception with Synthetic Data#1034480
Record · ID 1470028
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