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biometrics
- 基于人脸和语音双通道的生物认证算法,已经通过编译,效果较好。-based on human face and voice of biological dual-channel authentication algorithms, compiler has been passed, the result is better.
xibaoshibiexitong
- 细胞识别系统的实现,涉及到了图像处理知识,和生物细胞知识-cell recognition system to achieve that involves knowledge of image processing, and knowledge of biological cells
Gabor
- Gabor变换属于加窗傅立叶变换,Gabor函数可以在频域不同尺度、不同方向上提取相关的特征。另外Gabor函数与人眼的生物作用相仿,所以经常用作纹理识别上,并取得了较好的效果。-Gabor transform belongs to the windowed Fourier transform, Gabor function can be in the frequency domain on different scales and different directions extract re
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- 人脸识别是近年来模式识别、图像处理、机器视 觉、神经网络以及认知科学等领域研究的热点课题之 一。作为生物特征识别的一个重要方面, 人脸识别在 档案管理系统、安全验证系统、信用卡验证、公安系统 的罪犯身份识别、银行和海关的监控、人机交互等领域 具有广阔的应用前景。与指纹识别、视网膜识别、虹膜 识别等技术相比, 人脸识别技术在数据采集方面手续 比较简单, 使用者更容易接受。-Face recognition in recent years, pattern recogni
MathematicsofShapeDescriptionAMorphologicalApproac
- 在图像处理中形状描述通常是一件比较困难的事情,这本书用Morphological的方法对形状进行描述,以便于进一步进行图像的模式识别和理解。-The computer descr iption of shape and the computer manipulation of shape is complex simply because shape itself is complex. Of course, if the world of shape were limited to the
FaceDetect
- 人脸识别特指利用分析比较人脸视觉特征信息进行身份鉴别的计算机技术。人脸识别是一项热门的计算机技术研究领域,它属于生物特征识别技术,是对生物体(一般特指人)本身的生物特征来区分生物体个体。-Comparison of the use of face recognition especially the visual characteristics of facial identification information of computer technology. Face recognitio
Community-structure
- 复杂网络社团结构的识别算法GN算法,2002年提出-community structure in social and biological networks
rlsb
- 人脸识别特指利用分析比较人脸视觉特征信息进行身份鉴别的计算机技术。人脸识别是人脸识别C语言源代码。一项热门的计算机技术研究领域,它属于生物特征识别技术,是对生物体(一般特指人)本身的生物特征来区分生物体个体。 -The face recognition especially face visual features of the analysis and comparison of information for the identification of computer technolo
shenfenshibie
- 身份识别的相关文献。几种生物身份识别,主要是心音-The identification of the related literature. Several biological identity recognition, and mainly heart sounds
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- 基于指纹和手背静脉的双模态生物识别系统研究,很经典的论文-Based on fingerprint and hand vein multimode biological recognition system research, it was a classic papers
