@inproceedings{d8e410f1d3a54ca1a3ff59daefb763e4,
title = "Evolutionary algorithms meet classical and deep machine learning for skin detection in color images",
abstract = "Skin detection in color images has become an active research topic due to its numerous practical applications. In this paper, we couple classical and deep machine learning, together with an evolutionary training set selection algorithm for this task, and build an end-to-end pipeline that can flexibly benefit from such techniques. The experiments indicate that our approach can deliver accurate skin detection in a short time that may be generalized over different datasets, and that evolutionary training set selection can play a key role to allow for training the models from large training data.",
keywords = "deep learning, machine learning, memetic algorithm, skin detection",
author = "Jakub Nalepa and Stanislaw Czembor and Wojciech Dudzik and Michal Kawulok",
note = "Publisher Copyright: {\textcopyright} 2022 Owner/Author.; 2022 Genetic and Evolutionary Computation Conference Companion , GECCO 2022 ; Conference date: 09-07-2022 Through 13-07-2022",
year = "2022",
month = jul,
day = "9",
doi = "10.1145/3520304.3533941",
language = "English",
series = "GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference",
publisher = "Association for Computing Machinery, Inc",
pages = "67--68",
booktitle = "GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference",
}