arXiv (All)
open access
Type-Balanced Federated Learning for Visual Analog Meter Reading
Analog dial meters are widely deployed in industrial applications and utility sites, where environments and meter types vary and inspection data may be sensitive. Currently, automatic meter readers must be individually developed and deployed for each environment and meter type in practice. Deep lear
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
- Recursive Admissibility Architecture: A Structural Bridge from Internal System Dynamics to Domain Behaviour#79199
- Images supporting 'Fully automated platelet differential interference contrast image analysis via deep learning'#393686
- nvidia/Granary#786775
- The Vote Hides the Failure: Aggregation Choice and Noise Robustness in Heart Murmur Detection#1132362
- VTV-FM: Flow Matching through Variational Terminal-Velocity Closure#1155720
Record · ID 1115954
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