# SWL-Adapt: An Unsupervised Domain Adaptation Model with Sample Weight Learning for Cross-User Wearable Human Activity Recognition

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/swl-adapt-an-unsupervised-domain-adaptation-model-with-sample-weight-learning/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Rong Hu,Ling Chen,Shenghuan Miao,Xing Tang |
| Citations | 40 |
| DOI | 10.1609/aaai.v37i5.25743 |
| Fields | Computer Science |
| Open Access | true |
| OA Status | diamond |
| OA URL | https://ojs.aaai.org/index.php/AAAI/article/download/25743/25515 |
| OpenAlex ID | https://openalex.org/W4382239371 |
| Type | conference-paper |
| Year | 2023 |

## Paper authors

- [Xing Tang](https://scholariq.org/researchers/xing-tang/)

## Paper primary topic

- [Context-Aware Activity Recognition Systems](https://scholariq.org/topics/context-aware-activity-recognition-systems/)

## Paper topics

- [Context-Aware Activity Recognition Systems](https://scholariq.org/topics/context-aware-activity-recognition-systems/)
- [Human Pose and Action Recognition](https://scholariq.org/topics/human-pose-and-action-recognition/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.