Comparison of Several Features of Building Detection in Remote Sensing Image

DOI

10.2991/icmii-15.2015.55How to use a DOI?

Keywords

remote sensing; building detection; Haar; LBP; machine learning; deep learning; AdaBoost; evaluation

Abstract

AdaBoost algorithm based on Haar features and Local Binary Patterns (LBP features are widely used in machine learning method, and deep learning algorithm is a hot research field in recent years. Remote sensing image recognition meets the needs of human beings in the social development of Information Technology Intelligent. Combined machine learning method with the three features, a certain number of buildings in the remote sensing image were trained and performance test, and then the test results were evaluated, respectively. The results show that the features performance of the deep learning algorithm is better than the other two kinds of features, and the accuracy can meet the requirements of the application of remote sensing image interpretation.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Juncheng Wu
AU  - Jingwen Xu
AU  - Junfang Zhao
AU  - Ning Li
AU  - Surong Xiang
PY  - 2015/10
DA  - 2015/10
TI  - Comparison of Several Features of Building Detection in Remote Sensing Image
BT  - Proceedings of the 3rd International Conference on Mechatronics and Industrial Informatics
PB  - Atlantis Press
SP  - 306
EP  - 309
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmii-15.2015.55
DO  - 10.2991/icmii-15.2015.55
ID  - Wu2015/10
ER  -