@inproceedings{bd76ab9315634f3692c537a4aaec7e2e,
title = "Multi-objective evolutionary based feature selection supported by distributed multi-label classification and deep learning on image/video data",
abstract = "We live in an era in which a myriad of computer systems produce immense amounts of (raw) data every day. This big data must be processed efficiently to gain valuable and hidden knowledge. Complex processing pipelines need to be designed for filtering out irrelevant data, also for efficient data mining and machine learning methods must be used to discover useful correlations in the big data. The purpose of this PhD research is the implementation of multi-objective evolutionary-based dimensionality reduction on a high volume of image/video data with the support of distributed multi-label classification algorithms. ",
keywords = "big data processing, dimensionality reduction, distributed machine learning, feature engineering, feature extraction",
author = "Karagoz, {Gizem Nur}",
year = "2021",
doi = "10.1145/3491087.3493675",
language = "English",
series = "Middleware 2021 Doctoral Symposium - Proceedings of the 22nd International Middleware Conference: Doctoral Symposium",
publisher = "Association for Computing Machinery (ACM)",
pages = "6--7",
booktitle = "Middleware 2021 Doctoral Symposium - Proceedings of the 22nd International Middleware Conference",
address = "United States",
note = "22nd International Middleware Conference, Middleware 2021 ; Conference date: 06-12-2021 Through 10-12-2021",
}