  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.
