# EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videos

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/endonet-a-deep-architecture-for-recognition-tasks-on-laparoscopic-videos/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Andru Putra Twinanda,Sherif Shehata,Didier Mutter,Jacques Marescaux,Michel de Mathelin,Nicolas Padoy |
| Citations | 1,070 |
| DOI | 10.1109/tmi.2016.2593957 |
| Fields | Computer Science,Medicine |
| Open Access | true |
| OA Status | green |
| OA URL | https://hal.science/hal-03511473v1/document |
| OpenAlex ID | https://openalex.org/W2266464013 |
| PMID | 27455522 |
| Type | article |
| Year | 2016 |

## Paper authors

- [Michel de Mathelin](https://scholariq.org/researchers/michel-de-mathelin/)
- [Jacques Marescaux](https://scholariq.org/researchers/jacques-marescaux/)

## 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/)
- [Colorectal Cancer Screening and Detection](https://scholariq.org/topics/colorectal-cancer-screening-and-detection/)
- [Medical Image Segmentation Techniques](https://scholariq.org/topics/medical-image-segmentation-techniques/)

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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.