Dual Teaching: A Practical Semi-supervised Wrapper Method

no code implementations • 12 Nov 2016 • Fuqaing Liu, Chenwei Deng, Fukun Bi, Yiding Yang

Semi-supervised wrapper methods are concerned with building effective supervised classifiers from partially labeled data.

Object Recognition Based on Amounts of Unlabeled Data

no code implementations • 25 Mar 2016 • Fuqiang Liu, Fukun Bi, Liang Chen

Using 2% labeled data and 98% unlabeled data, the accuracies of the proposed method on the two data sets are 78. 39% and 50. 77% respectively.

Object Object Recognition

Feature-Area Optimization: A Novel SAR Image Registration Method

no code implementations • 18 Feb 2016 • Fuqiang Liu, Fukun Bi, Liang Chen, Hao Shi, Wei Liu

This letter proposes a synthetic aperture radar (SAR) image registration method named Feature-Area Optimization (FAO).

Image Registration

Boost Picking: A Universal Method on Converting Supervised Classification to Semi-supervised Classification

no code implementations • 18 Feb 2016 • Fuqiang Liu, Fukun Bi, Yiding Yang, Liang Chen

It is theoretically proved that Boost Picking could train a supervised model mainly by un-labeled data as effectively as the same model trained by 100% labeled data, only if recalls of the two weak classifiers are all greater than zero and the sum of precisions is greater than one.

Classification General Classification