# MS-TCRNet: Multi-Stage Temporal Convolutional Recurrent Networks for Action Segmentation Using Sensor-Augmented Kinematics

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/ms-tcrnet-multi-stage-temporal-convolutional-recurrent-networks-for-action/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Adam Goldbraikh,Omer Shubi,Or Rubin,Carla M. Pugh,Shlomi Laufer |
| Citations | 2 |
| DOI | 10.48550/arxiv.2303.07814 |
| Fields | Engineering,Medicine |
| Open Access | true |
| OA Status | green |
| OA URL | https://arxiv.org/pdf/2303.07814 |
| OpenAlex ID | https://openalex.org/W4327525264 |
| Type | preprint |
| Year | 2023 |

## Paper authors

- [Adam Goldbraikh](https://scholariq.org/researchers/adam-goldbraikh/)

## Paper journal

- [arXiv (Cornell University)](https://scholariq.org/journals/arxiv-cornell-university/)

## Paper primary topic

- [Surgical Simulation and Training](https://scholariq.org/topics/surgical-simulation-and-training/)

## Paper topics

- [Surgical Simulation and Training](https://scholariq.org/topics/surgical-simulation-and-training/)
- [Anatomy and Medical Technology](https://scholariq.org/topics/anatomy-and-medical-technology/)
- [Medical Imaging and Analysis](https://scholariq.org/topics/medical-imaging-and-analysis/)

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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.