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Automatic 3D face recognition from depth and intensity Gabor features 期刊论文
PATTERN RECOGNITION, 2009, 卷号: 42, 期号: 9, 页码: 1895-1905
作者:  Xu, Chenghua;  Li, Stan;  Tan, Tieniu;  Quan, Long
收藏  |  浏览/下载：23/0  |  提交时间：2015/08/12
Ensemble component selection for improving ICA based microarray data prediction models 期刊论文
http://dx.doi.org/10.1016/j.patcog.2009.01.021, 2009
Liu, Kun-Hong; Li, Bo; Zhang, Jun; Du, Ji-Xiang; 刘昆宏
收藏  |  浏览/下载：3/0  |  提交时间：2015/07/22
汉语CALL系统声调语调评估诊断技术研究 学位论文
工学博士, 中国科学院自动化研究所: 中国科学院研究生院, 2009
作者:  柯登峰
收藏  |  浏览/下载：46/0  |  提交时间：2015/09/02
基于图像特征的多尺度变换图像融合技术研究 学位论文
长春光学精密机械与物理所: 中国科学院长春光学精密机械与物理所, 2009
作者:  武治国
收藏  |  浏览/下载：6/0  |  提交时间：2012/03/21
复杂背景下的目标实时分割与检测 学位论文
工学博士, 中国科学院自动化研究所: 中国科学院研究生院, 2009
作者:  吴晓雨
收藏  |  浏览/下载：91/0  |  提交时间：2015/09/02
指纹识别中几个实用问题的研究 学位论文
工学博士, 中国科学院自动化研究所: 中国科学院研究生院, 2009
作者:  张阳阳
收藏  |  浏览/下载：52/0  |  提交时间：2015/09/02
Rana grylio virus thymidine kinase gene: an early gene of iridovirus encoding for a cytoplasmic protein 期刊论文
VIRUS GENES, 2009, 卷号: 38, 期号: 2, 页码: 345-352
作者:  Zhao, Zhe;  Ke, Fei;  Shi, Yan;  Zhou, Guang-;  Gui, Jian-Fang
收藏  |  浏览/下载：40/0  |  提交时间：2010/10/13
A genetic programming-based approach to the classification of multiclass microarray datasets 期刊论文
http://dx.doi.org/10.1093/bioinformatics/btn644, 2009
Liu, Kun-Hong; Xu, Chun-Gui; 刘昆宏
收藏  |  浏览/下载：2/0  |  提交时间：2015/07/22
Using bidirectional binary particle swarm optimization for feature selection in feature-level fusion recognition system (EI CONFERENCE) 会议论文
2009 4th IEEE Conference on Industrial Electronics and Applications, ICIEA 2009, May 25, 2009 - May 27, 2009, Xi'an, China
Wang D.; Ge W.; Wang Y.
收藏  |  浏览/下载：16/0  |  提交时间：2013/03/25
In feature-level fusion recognition system  the other is optimizing system sensor design to get outstanding cost performance. So feature selection become usually necessary to reduce dimensionality of the combination of multi-sensor features and improve system performance in system design. In general  there are two main missions. One is improving the recognition correct rate as soon as possible  the optimization is usually applied to feature selection because of its computational feasibility and validity. For further improving recognition accuracy and reducing selected feature dimensions  this paper presents a more rational and accurate optimization  Bidirectional Binary Particle Swarm Optimization (BBPSO) algorithm for feature selection in feature-level fusion target recognition system. In addition  we introduce a new evaluating function as criterion function in BBPSO feature selection method. At the last  we utilized Leave-One-Out method to validate the proposed method. The experiment results show that the proposed algorithm improves classification accuracy by two percentage points  while the selected feature dimensions are less one dimension than original Particle Swarm Optimization approach with 16 original feature dimensions. 2009 IEEE.  
Assessment of color image fusion algorithms based on quaternion singular value decomposition (EI CONFERENCE) 会议论文
MIPPR 2009 - Remote Sensing and GIS Data Processing and Other Applications: 6th International Symposium on Multispectral Image Processing and Pattern Recognition, October 30, 2009 - November 1, 2009, Yichang, China
Wang Y.; Zhu M.; Pang H.; Wang Y.
收藏  |  浏览/下载：16/0  |  提交时间：2013/03/25
In this paper  a new approach to objectively assess the performance of image fusion algorithms is proposed. It is based on the quaternion representation for the structural information of color images. Quaternions are used to encode the pixels of a color image into a quaternion matrix. Local variance of the luminance layer of color image is taken as the real part of a quaternion  then the three RGB channels of the color image are encoded into the three imaginary parts of the quaternion. The angle between the singular value feature vectors of the quaternion matrices corresponding to the source image and the fused image is used to measure the structural similarity of them. Different weight is given to the source images by using variance. The experiment results show that the proposed assessment method is consistent with the HVS. The color information of a color image can be fully used by this method. It can give an accurate assessment result for each fusion algorithm by using the source images and the fused image. 2009 Copyright SPIE - The International Society for Optical Engineering.  

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