@inproceedings{e6c0ccf1f0a546c0be12fe6467cdd594,
title = "Study on Remote Sensing Image Vegetation Classification Method Based on Decision Tree Classifier",
abstract = "Aiming at the problem of inaccurate classification of forest vegetation, this paper presents a study on possible method for remote sensing from images. As classifiers we have used decision tree methods based on the idea of Boost Tree, Ada Tree and C5 approaches. For the experiments we have used single decision tree generation method for which training tuples are generated by sampling. In experiments we tried to evaluate how classifications work for agriculture images.",
keywords = "Composite decision, remote sensing, vegetation",
author = "Wei Wei and Dawid Poap and Xiaohua Li and Marcin Wo{\'z}niak and Junzhe Liu",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 8th IEEE Symposium Series on Computational Intelligence, SSCI 2018 ; Conference date: 18-11-2018 Through 21-11-2018",
year = "2018",
month = jul,
day = "2",
doi = "10.1109/SSCI.2018.8628721",
language = "English",
series = "Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2292--2297",
editor = "Suresh Sundaram",
booktitle = "Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018",
address = "United States",
}