Multi-Plateau Ensemble for Endoscopic Artefact Segmentation and Detection

03/23/2020
by   Suyog Jadhav, et al.
1

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.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
01/18/2021

HarDNet-MSEG: A Simple Encoder-Decoder Polyp Segmentation Neural Network that Achieves over 0.9 Mean Dice and 86 FPS

We propose a new convolution neural network called HarDNet-MSEG for poly...
research
06/14/2022

A Multi-task Framework for Infrared Small Target Detection and Segmentation

Due to the complicated background and noise of infrared images, infrared...
research
11/26/2021

Efficient Self-Ensemble Framework for Semantic Segmentation

Ensemble of predictions is known to perform better than individual predi...
research
08/15/2021

The Marine Debris Dataset for Forward-Looking Sonar Semantic Segmentation

Accurate detection and segmentation of marine debris is important for ke...
research
07/20/2020

Improving Semantic Segmentation via Decoupled Body and Edge Supervision

Existing semantic segmentation approaches either aim to improve the obje...
research
08/04/2023

Deep Semantic Model Fusion for Ancient Agricultural Terrace Detection

Discovering ancient agricultural terraces in desert regions is important...
research
12/24/2021

Deep ensembles in bioimage segmentation

Semantic segmentation consists in classifying each pixel of an image by ...

Please sign up or login with your details

Forgot password? Click here to reset