Parameterising the SA-UNet using a Genetic Algorithm

Mahsa Mahdinejad, Aidan Murphy, Patrick Healy, Conor Ryan

2022

Abstract

Deep learning is an excellent way for effectively addressing image processing, and several Neural Networks designs have been explored in this area. The Spatial Attention U-Net architecture, a version of the famous U-Net but which uses DropBlock and an attention block as well as the common U-Net convolutional blocks, is one notable example. Finding the best combination of hyper-parameters is expensive, time consuming and needs expert input. We show the genetic algorithm can be utilized to automatically determine the optimal combination of Spatial Attention U-Net hyper-parameters to train a model to solve a Retinal Blood Vessel Segmentation problem. Our new approach is able to find a model with an accuracy measure of 0.9855, an improvement from our previous experimentation which found a model with accuracy measure of 0.9751. Our new methods exhibit competitive performance with other state-of-the-art Retinal Blood Vessel Segmentation techniques.

Paper Citation

in Harvard Style

Mahdinejad M., Murphy A., Healy P. and Ryan C. (2022). Parameterising the SA-UNet using a Genetic Algorithm. In Proceedings of the 14th International Joint Conference on Computational Intelligence (IJCCI 2022) - Volume 1: ECTA; ISBN 978-989-758-611-8, SciTePress, pages 97-104. DOI: 10.5220/0011528100003332

in Bibtex Style

@conference{ecta22,
author={Mahsa Mahdinejad and Aidan Murphy and Patrick Healy and Conor Ryan},
title={Parameterising the SA-UNet using a Genetic Algorithm},
booktitle={Proceedings of the 14th International Joint Conference on Computational Intelligence (IJCCI 2022) - Volume 1: ECTA},
year={2022},
pages={97-104},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011528100003332},
isbn={978-989-758-611-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computational Intelligence (IJCCI 2022) - Volume 1: ECTA
TI - Parameterising the SA-UNet using a Genetic Algorithm
SN - 978-989-758-611-8
AU - Mahdinejad M.
AU - Murphy A.
AU - Healy P.
AU - Ryan C.
PY - 2022
SP - 97
EP - 104
DO - 10.5220/0011528100003332
PB - SciTePress