Abdul Qadir Khan1, Guangmin Sun1,*, Yu Li1, Anas Bilal2, Malik Abdul Manan1
CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2481-2504, 2023, DOI:10.32604/cmc.2023.043239
- 29 November 2023
Abstract In the emerging field of image segmentation, Fully Convolutional Networks (FCNs) have recently become
prominent. However, their effectiveness is intimately linked with the correct selection and fine-tuning of hyperparameters, which can often be a cumbersome manual task. The main aim of this study is to propose a more
efficient, less labour-intensive approach to hyperparameter optimization in FCNs for segmenting fundus images.
To this end, our research introduces a hyperparameter-optimized Fully Convolutional Encoder-Decoder Network
(FCEDN). The optimization is handled by a novel Genetic Grey Wolf Optimization (G-GWO) algorithm. This
algorithm employs the Genetic Algorithm (GA) to… More >