@inproceedings{dcc4936093074f8cb9aa243e3e6a4817,
title = "Efficient visual classification by fuzzy rules",
abstract = "The paper proposes a method for classifying and fast retrieving images which uses boosting metalearning to search for the most salient image features. We use local image keypoints as image features. We construct by boosting a set fuzzy rules describing image feature parameters. The rules constitute a set of weak classifiers voting for the final image class. The method can use various image features, engineered and learned by deep learning methods. We checked the methods on some real-world images.",
keywords = "Boosting, Content-based image retrieval, Fuzzy rules, Image keypoints",
author = "Marcin Korytkowski and Rafal Scherer and Dominik Szajerman and Dawid Polap and Marcin Wozniak",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2020 ; Conference date: 19-07-2020 Through 24-07-2020",
year = "2020",
month = jul,
doi = "10.1109/FUZZ48607.2020.9177777",
language = "English",
series = "IEEE International Conference on Fuzzy Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2020 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2020 - Proceedings",
address = "United States",
}