Surface object recognition with CNN and SVM in Landsat 8 images

Tomohiro Ishii, Ryosuke Nakamura, Hidemoto Nakada, Yoshihiko Mochizuki, Hiroshi Ishikawa

研究成果: Conference contribution

29 被引用数 (Scopus)

抄録

There is a series of earth observation satellites called Landsat, which send a very large amount of image data every day such that it is hard to analyze manually. Thus an effective application of machine learning techniques to automatically analyze such data is called for. In surface object recognition, which is one of the important applications of such data, the distribution of a specific object on the surface is surveyed. In this paper, we propose and compare two methods for surface object recognition, one using the convolutional neural network (CNN) and the other support vector machine (SVM). In our experiments, CNN showed higher performance than SVM. In addition, we observed that the number of negative samples have a influence on the performance, and it is necessary to select the number of them for practical use.

本文言語English
ホスト出版物のタイトルProceedings of the 14th IAPR International Conference on Machine Vision Applications, MVA 2015
出版社Institute of Electrical and Electronics Engineers Inc.
ページ341-344
ページ数4
ISBN(電子版)9784901122153
DOI
出版ステータスPublished - 2015 7 8
イベント14th IAPR International Conference on Machine Vision Applications, MVA 2015 - Tokyo, Japan
継続期間: 2015 5 182015 5 22

出版物シリーズ

名前Proceedings of the 14th IAPR International Conference on Machine Vision Applications, MVA 2015

Other

Other14th IAPR International Conference on Machine Vision Applications, MVA 2015
CountryJapan
CityTokyo
Period15/5/1815/5/22

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Vision and Pattern Recognition

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