This method combines the ideas of two-dimensional clustering-based discriminant analysis (2DCDA) and maximum scatter difference (MSD), which can directly ...

Abstract. In this paper, a novel image feature extraction technique, called two-dimensional maximum clustering-based scatter difference (2DMCSD) dis-.

Liping Hu, Hongwei Liu, Shunjun Wu: Two-Dimensional Maximum Clustering-Based Scatter Difference Discriminant Analysis for Synthetic Aperture Radar Automatic ...

This paper gives a new image feature extraction technique coined two-dimensional clustering-based discriminant analysis (2DCDA), which is based on 2D image ...

This paper introduces a novel framework for 3D head model recognition based on the recently proposed 2D subspace analysis method.

This method combines the ideas of two-dimensional clustering-based discriminant analysis (2DCDA) and maximum scatter difference (MSD), which can directly ...

Experimental results based on MSTAR data indicate that two-stage 2DPCA can decrease feature dimensions significantly, and the target recognition performance ...

A new estimation strategy on locations of two-dimensional target scattering centers for radar target recognition is developed by using multiple ...

Two-Dimensional Maximum Clustering-Based Scatter Difference Discriminant Analysis for Synthetic Aperture Radar Automatic Target Recognition · Computer Science, ...

SAR ATR involves a sequence of processes, such as some type of preprocessing, feature extraction, classifier construction, and finally target classification.