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.
@article{arxiv.2003.10129,
title = {Multi-Plateau Ensemble for Endoscopic Artefact Segmentation and Detection},
author = {Suyog Jadhav and Udbhav Bamba and Arnav Chavan and Rishabh Tiwari and Aryan Raj},
journal= {arXiv preprint arXiv:2003.10129},
year = {2020}
}