In previous optimization-based methods of 3D planar-faced object reconstruction from single 2D line drawings, the missing depths of the vertices of a line drawing (and other parame...
The null space N(St) of total scatter matrix St contains no useful information for pattern classification. So, discarding the null space N(St) results in dimensionality reduction ...
Wen-Sheng Chen, Pong Chi Yuen, Jian Huang, Jian-Hu...
The null space-based LDA takes full advantage of the null space while the other methods remove the null space. It proves to be optimal in performance. From the theoretical analysi...
The null space of the within-class scatter matrix is found to express most discriminative information for the small sample size problem (SSSP). The null space-based LDA takes full ...
While null space based linear discriminant analysis (NLDA) obtains a good discriminant performance, the ability easily suffers from an implicit assumption of Gaussian model with sa...
Abstract—In an OFDM receiver with direct-conversion architecture, DC offset (DCO) and carrier frequency offset (CFO) cause a severe performance degradation. Recently, by investig...
Hai Lin, Takeshi Nakao, Weiming Lu, Katsumi Yamash...
This paper presents a novel classification/ retrieval system for motion events based on a perfect view invariant representation of motion trajectories and a linear classifier al...
Eser Ustunel, Xu Chen, Dan Schonfeld, Ashfaq A. Kh...
In this paper, we propose a novel general framework for tensor based null space affine invariants, namely, tensor null space invariants (TNSI) with a linear classifier for high ...
Event/object classification and recognition is an extremely challenging problem, particularly when the query or stored data undergo an affine transformation due to camera motion. ...