@inproceedings{f29b05a2ff654e3f9636fa9f98d45da4,
title = "A MKL-MKB image classification algorithm based on multi-kernel boosting method",
abstract = "Aiming at the low accuracy and poor applicability of traditional SVM classifiers, this paper proposes an image classification system based on MKLMKB (multi kernel learning-multi kernel boosting). This approach firstly integrates existing feature extraction methods to extract features like wavelet, Gabor, GLCM and so on. A weak classifier is constructed by using a synthetic kernel in kernel space. We use Nystrom approximation algorithm to calculate weights of kernel matrixes of multi-kernel model. Then we make a decision level fusion of weak classifiers under Adaboost framework to impair weights of weak kernels. Finally, experiments are carried out to verify the validity and applicability of the proposed algorithm by testing on terrain remote sensing images and several UCI data sets.",
keywords = "Adaboost, Image classification, Multi-kernel, SVM",
author = "Ni Li and Wenqing Huai and Guanghong Gong",
note = "Publisher Copyright: {\textcopyright} Springer Science+Business Media Singapore 2016.; 16th Asia Simulation Conference and SCS Autumn Simulation Multi-Conference, AsiaSim/SCS AutumnSim 2016 ; Conference date: 08-10-2016 Through 11-10-2016",
year = "2016",
doi = "10.1007/978-981-10-2663-8\_17",
language = "英语",
isbn = "9789811026621",
series = "Communications in Computer and Information Science",
publisher = "Springer Verlag",
pages = "156--164",
editor = "Lin Zhang and Xiao Song and Yunjie Wu",
booktitle = "Theory, Methodology, Tools and Applications for Modeling and Simulation of Complex Systems - 16th Asia Simulation Conference and SCS Autumn Simulation Multi-Conference, AsiaSim/SCS AutumnSim 2016, Proceedings",
address = "德国",
}