1.
An Algorithm for Face Recognition with Single Training Image per Person Based on Associative Memory Neural Network
一种基于联想记忆神经网络的单训练样本人脸识别算法
2.
Research on Face Recognition with Single Training Image Per Person
单训练样本条件下人脸识别技术研究
3.
Face recognition from single sample per class based on Gabor filtering
基于Gabor变换的每类单个训练样本人脸识别研究
4.
Face Recognition Researches on Large Scale and Each Person with Few Samples;
大类别及少量训练样本的人脸识别问题研究
5.
A Single Training Sample Face Recognition Based on Modular Weighted (2D)~2PCA;
基于分块加权（2D）~2PCA的单样本人脸识别
6.
Sub-block face recognition based on virtual information with one training image per person
基于虚拟信息的单样本分块人脸识别
7.
Study of Single Sample Problem of Face Recognition Based on Gabor Wavelet;
基于Gabor小波的人脸识别的单样本问题研究
8.
Towards Face Recognition from One Single Training Sample Per Person Using Algebraic Features;
单样本条件下基于代数特征的人脸识别研究
9.
Pose and Illumination Invariant Face Recognition Based on HMM with One Sample Per Person
基于HMM的单样本可变光照、姿态人脸识别
10.
Sub-block Face Recognition Method Based on Virtual Information with One Training Image per Person
基于虚拟信息的单样本分块人脸识别方法
11.
Research on the Technology of Face Recognition with Single Sample Based on Generated Virtual Image and Fusion HMM
基于虚拟图像生成与融合HMM的单样本人脸识别技术研究
12.
Face Image Feature Extraction and Recognition in the Case of Small Sample Size Problem
小样本人脸图像特征抽取和识别方法研究
13.
Click Train Now to train the Category Assistant to recognize categories when creating a content index. The training set consists of all current categories.
单击“开始训练”可以训练“分类助手”在创建内容索引时识别类别。训练集由所有当前类别组成。
14.
The standard large face database is required to verity the performance of face detection and recognition algorithm.
为了检验面像检测和识别算法的优劣,需要有大量的人脸样本。
15.
Study on Large-Scale Dataset and Multimodal Image Fusion Methods in Face Recognition;
人脸识别中的大样本集问题及多模式图像融合方法的研究
16.
Multipose Face Recognition Based on Eigenspace
基于本征空间的多姿态人脸识别方法
17.
Research on Single Face Recognition System Based on LDA;
基于线性判别分析的单人脸识别系统研究
18.
Click Train Now to train the Category Assistant to recognize areas when creating a content index. The training set consists of all current areas.
单击“开始训练”可以训练“分类助手”在创建内容索引时识别区域。训练集由所有当前区域组成。