SHU Research Data Archive (SHURDA)
metadata only
VISTA, Visual and Inertial Sensor for recogniTion of human Activities
Over the last years, human activity recognition has gained considerable success due to the importance to understand what a person is doing during normal daily activities. The correct understanding of human-being activities is playing a fundamental role also in the field of Human-robot interaction.
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
- Motionscope AI: comprehensive human activity recognition through integrated pose analysis and temporal modeling#293278
- Easy Ensemble: Simple Deep Ensemble Learning for Sensor-Based Human Activity Recognition#174004
- Easy Ensemble: Simple Deep Ensemble Learning for Sensor-Based Human Activity Recognition#173426
- Easy Ensemble: Simple Deep Ensemble Learning for Sensor-Based Human Activity Recognition#173176
- Easy Ensemble: Simple Deep Ensemble Learning for Sensor-Based Human Activity Recognition#172160
Record · ID 1019263
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