@inproceedings{297f2bd93f8f4d9bb84d784ba02222a8,
title = "Tile2Vec with Predicting Noise for Land Cover Classification",
abstract = "Tile2vec has proven to be a good representation learning model in the remote sensing field. The success of the model depends on l2-norm regularization. However, l2-norm regularization has the main drawback that affects the regularization. We propose to replace the l2-norm with regularization with predicting noise framework. We then develop an algorithm to integrate the framework. We evaluate the model by using it as a feature extractor on the land cover classification task. The result shows that our proposed model outperforms all the baseline models.",
keywords = "Deep learning, Land cover classification, Predicting noise, Remote sensing, Representation learning, Tile2vec",
author = "Sinaga, {Marshal Arijona} and Ali, {Fadel Muhammad} and Arymurthy, {Aniati Murni}",
note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG.; 28th International Conference on Neural Information Processing, ICONIP 2021 ; Conference date: 08-12-2021 Through 12-12-2021",
year = "2021",
doi = "10.1007/978-3-030-92273-3_8",
language = "English",
isbn = "9783030922726",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "87--99",
editor = "Teddy Mantoro and Minho Lee and Ayu, {Media Anugerah} and Wong, {Kok Wai} and Hidayanto, {Achmad Nizar}",
booktitle = "Neural Information Processing - 28th International Conference, ICONIP 2021, Proceedings",
address = "Germany",
}