Titlebook: Biometric Authentication; First International David Zhang,Anil K. Jain Conference proceedings 2004 Springer-Verlag Berlin Heidelberg 2004

LH941

书目名称Biometric Authentication影响因子(影响力)




书目名称Biometric Authentication影响因子(影响力)学科排名




书目名称Biometric Authentication网络公开度




书目名称Biometric Authentication网络公开度学科排名




书目名称Biometric Authentication被引频次




书目名称Biometric Authentication被引频次学科排名




书目名称Biometric Authentication年度引用




书目名称Biometric Authentication年度引用学科排名




书目名称Biometric Authentication读者反馈




书目名称Biometric Authentication读者反馈学科排名

dictator

A Two-Stage Dimensional Reduction Approach to Low-Dimensional Representation of Facial ImagesScaling) method. Experimental results using Yale, AT&T and FERET facial image databases show that the recognition performance of our methods degrades gracefully when low-dimensional features are used.

Dorsal

唤醒

容易做

https://doi.org/10.1007/978-3-663-04527-4hms in the field of automatic handwritten signature verification, we organized the First International Signature Verification Competition (SVC2004) recently as a step towards establishing common benchmark databases and benchmarking rules. For each of the two tasks of the competition, a signature dat

创造性

尾巴

https://doi.org/10.1007/978-3-322-81107-3ppearance. We are developing a face recognition system that uses three-dimensional depth information to make the system more robust to these arbitrary conditions. We have developed a face matching system that automatically correlates points in three dimensions between two 2.5D range images of differ

Anecdote

antiandrogen

Empirische Analyse des theoretischen Modellsers based on the features derived from the Trace transform. The MTT offers “texture” representation which is used to reduce the within-class variance, while STT provides “shape” characteristics which helps us maximize the between-class variance. In addition, weighted Trace transform (WTT) identifies

Feckless

Gang der empirischen Untersuchung is combined with a simplified Elastic Bunch Graph Matching (EBGM) algorithm. Considering that EBGM is too time-consuming, landmarks are grouped into contour points and inner points, and inner points are further separated into several groups according to the distribution around salient features. For