arXiv (All)
open access
SincDPNet: Interpretable Raw-Waveform Bathroom Activity Recognition for Assistive Living
Bathroom acoustic-event recognition can support ambient assisted living in settings where continuous video monitoring is undesirable. However, practical deployment requires models that are compact, interpretable, and robust to changes in the recording environment. This work introduces \dataset{}, a
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
- MBP-NET: Motion-Background Disentanglement Network for Lightweight Video Action Recognition#381260
- "What's That Sound?": A Versatile, Robust, and Lightweight Convolutional Transformer for Environment Sound Recognition#1064306
- 3rd Place Solution to Human Motion Challenges in Real-World and Clinical Settings (MoCha) @ECCV2026: Language-Aligned Motion Representations for Domain-Generalizable UPDRS-Gait Severity Estimation#998453
- PSEE: Progressive Sensor Event Expansion for Point-Supervised Temporal Action Localization#1035862
- Glasgow CCTV Object Detection Data#325620
Record · ID 1129518
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