An Image Classification Method based on Improved Active Learning and Semi-supervised Learning Algorithm

Title:An Image Classification Method based on Improved Active Learning and Semi-supervised Learning Algorithm

Volume: 11 Issue: 3

Author(s): Dan Luo*

Affiliation:

• School of Computer Science, Shaanxi Normal University, XiAn 710119,China

Keywords: Improved active learning, semi-supervised learning algorithm, support vector machine, image classification method, Bayesian classifier, flexible neural tree.

Abstract: Background: It presents a kind of multi-class image classification algorithm which is combined with Best Versus Second Best (BVSB) active learning technology and improved self-training semi-supervised learning technology.

Methods: The algorithm integrates the advantages of active learning; semi-supervised learning and extreme learning machine simultaneously. It has better performance than that of single algorithm when it is used in different sets of image target recognition.

Results: In addition, it also discussed the influence of various parameters on the algorithm performance in the experimental parts, and made related analysis of semi-supervised learning algorithm based on SVM (Support Vector Machine); the experimental results verified the superiority of proposed algorithm.

Cite this article as:

Luo Dan *, An Image Classification Method based on Improved Active Learning and Semi-supervised Learning Algorithm, Recent Advances in Electrical & Electronic Engineering 2018; 11 (3) . https://dx.doi.org/10.2174/2352096511666180116160240

DOI https://dx.doi.org/10.2174/2352096511666180116160240	Print ISSN 2352-0965
Publisher Name Bentham Science Publisher	Online ISSN 2352-0973