An Empirical Study of the Convolution Neural Networks Based Detection on Object With Ambiguous Boundary in Remote Sensing Imagery - A Case of Potential Loess Landslide.
Please log in to take part in the discussion (add own reviews or comments).
Cite this publication
More citation styles
- please select -
%0 Journal Article
%1 journals/staeors/YaoZLXWLJ22
%A Yao, Guangle
%A Zhou, Wenlong
%A Liu, Mingzhe
%A Xu, Qiang
%A Wang, Honghui
%A Li, Jun
%A Ju, Yuanzhen
%D 2022
%J IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens.
%K dblp
%P 323-338
%T An Empirical Study of the Convolution Neural Networks Based Detection on Object With Ambiguous Boundary in Remote Sensing Imagery - A Case of Potential Loess Landslide.
%U http://dblp.uni-trier.de/db/journals/staeors/staeors15.html#YaoZLXWLJ22
%V 15
@article{journals/staeors/YaoZLXWLJ22,
added-at = {2024-03-08T00:00:00.000+0100},
author = {Yao, Guangle and Zhou, Wenlong and Liu, Mingzhe and Xu, Qiang and Wang, Honghui and Li, Jun and Ju, Yuanzhen},
biburl = {https://www.bibsonomy.org/bibtex/219a1c5505d309d5ecb3a5a9f491b7232/dblp},
ee = {https://doi.org/10.1109/jstars.2021.3132416},
interhash = {acb83b18a8a39bb6d9fb1468effeeb5b},
intrahash = {19a1c5505d309d5ecb3a5a9f491b7232},
journal = {IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens.},
keywords = {dblp},
pages = {323-338},
timestamp = {2024-04-08T20:58:18.000+0200},
title = {An Empirical Study of the Convolution Neural Networks Based Detection on Object With Ambiguous Boundary in Remote Sensing Imagery - A Case of Potential Loess Landslide.},
url = {http://dblp.uni-trier.de/db/journals/staeors/staeors15.html#YaoZLXWLJ22},
volume = 15,
year = 2022
}
