TernausNet: U-Net with VGG11 Encoder Pre-Trained on ImageNet for Image Segmentation
By Vladimir Iglovikov and Alexey Shvets
Introduction
TernausNet is a modification of the celebrated UNet architecture that is widely used for binary Image Segmentation. For more details, please refer to our arXiv paper.
(Network architecure)
Pre-trained encoder speeds up convergence even on the datasets with a different semantic features. Above curve shows validation Jaccard Index (IOU) as a function of epochs for Aerial Imagery
This architecture was a part of the winning solutiuon (1st out of 735 teams) in the Carvana Image Masking Challenge.
Citing TernausNet
Please cite TernausNet in your publications if it helps your research:
@ARTICLE{arXiv:1801.05746,
author = {V. Iglovikov and A. Shvets},
title = {TernausNet: U-Net with VGG11 Encoder Pre-Trained on ImageNet for Image Segmentation},
journal = {ArXiv e-prints},
eprint = {1801.05746},
year = 2018
}