# SkeletonNet: Mining Deep Part Features for 3-D Action Recognition

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/skeletonnet-mining-deep-part-features-for-3-d-action-recognition/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Qiuhong Ke,Senjian An,Mohammed Bennamoun,Ferdous Sohel,Farid Boussaïd |
| Citations | 171 |
| DOI | 10.1109/lsp.2017.2690339 |
| Fields | Computer Science |
| Open Access | true |
| OA Status | green |
| OA URL | https://research-repository.uwa.edu.au/en/publications/40d02f55-7d02-47cd-8021-bdc09de25f10 |
| OpenAlex ID | https://openalex.org/W2602311553 |
| Type | article |
| Year | 2017 |

## Paper authors

- [Ferdous Sohel](https://scholariq.org/researchers/ferdous-sohel/)

## Paper primary topic

- [Human Pose and Action Recognition](https://scholariq.org/topics/human-pose-and-action-recognition/)

## Paper topics

- [Human Pose and Action Recognition](https://scholariq.org/topics/human-pose-and-action-recognition/)
- [Anomaly Detection Techniques and Applications](https://scholariq.org/topics/anomaly-detection-techniques-and-applications/)
- [Multimodal Machine Learning Applications](https://scholariq.org/topics/multimodal-machine-learning-applications/)

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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.