The problem of choosing a good parameter setting for a better generalization performance in a learning task is the so-called model selection. A nested uniform design (UD) methodol...
Chien-Ming Huang, Yuh-Jye Lee, Dennis K. J. Lin, S...
In this paper, a novel method for accurate subject tracking, by selecting only tracked subject boundary edges in a video stream with a changing background and moving camera, is pr...
Myung-Cheol Roh, Tae-Yong Kim, Jihun Park, Seong-W...
We have applied two state-of-the-art speech synthesis techniques (unit selection and HMM-based synthesis) to the synthesis of emotional speech. A series of carefully designed perc...
Roberto Barra-Chicote, Junichi Yamagishi, Simon Ki...
Negative selection algorithms are immune-inspired classifiers that are trained on negative examples only. Classification is performed by generating detectors that match none of ...
We present a vector selection methodology for estimating the peak power dissipation in a CMOS logic circuit. The ultimate goal is to combine the speed of RT-level simulation with ...