# Multi-Plateau Ensemble for Endoscopic Artefact Segmentation and Detection

arXiv: https://arxiv.org/abs/2003.10129 · HTML: https://mlsanity.com/paper/2003.10129/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Mar 2020.

## Built on by (most cited first, 1 of 1)

- [Evaluating object detector ensembles for improving the robustness of artifact detection in endoscopic video streams](https://mlsanity.com/paper/2206.07580/) (2022)

## Abstract (arXiv)

Endoscopic artefact detection challenge consists of 1) Artefact detection, 2) Semantic segmentation, and 3) Out-of-sample generalisation. For Semantic segmentation task, we propose a multi-plateau ensemble of FPN (Feature Pyramid Network) with EfficientNet as feature extractor/encoder. For Object detection task, we used a three model ensemble of RetinaNet with Resnet50 Backbone and FasterRCNN (FPN + DC5) with Resnext101 Backbone}. A PyTorch implementation to our approach to the problem is available at https://github.com/ubamba98/EAD2020.