1.
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
2.
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
3.
Signature Verification Incorporating the Prior Model;
结合先验模型、无简单伪造训练样本的签名鉴定
4.
Construction Method for Training Data Set in Classification Algorithm of Support Vector Machines
支持向量机分类算法中训练样本集的构造方法
5.
Selection of Training Samples for SVM Based on AdaBoost Approach
基于AdaBoost方法的支持向量机训练样本选择
6.
Quantitative Measurement of Training Sample Capacity for Chinese Statistical Language Model
汉语统计语言模型训练样本容量的定量化度量
7.
Sample Reduction Strategy for SVM Large-scale Training Data Set Using PSO
利用粒子群算法缩减大规模数据集SVM训练样本
8.
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
9.
A Method for Reducing the Amount of Training Samples in KNN Text Classification Based on Clustering and Density
基于聚类和密度的KNN分类器训练样本约减方法
10.
In the training of the neural network model (NNM) of the plant and the neural network controller (NNC), training samples are got from the state function of the plant.
在训练实现对象模型的网络和实现控制器的网络时,由状态方程产生训练样本。
11.
A periodic function, finite Fourier series, is used to activate the actuator for obtaining training samples.
用周期函数,有限项傅立叶级数,作为激励函数来获取训练样本。
12.
The Selection of Classify Attribute from Web Page Training-set Base on Rough Sets;
基于粗糙集的网页训练样本集的分类属性的选择
13.
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
14.
New reduction strategy of large-scale training sample set for SVM
一种新的支持向量机大规模训练样本集缩减策略
15.
Construction of the Training Data Set in Intrusion Detection Systems Based on the Agglomerate Clustering Algorithm
入侵检测系统中基于凝聚聚类算法的训练样本集的构造
16.
WC-SVM ALGORITHM BASED ON TRAINING SETS PRE-PROCESSED BY FUZZY CLUSTERING ANALYSIS
基于模糊聚类分析预先处理训练样本的WC-SVM方法
17.
The Training Strategy of SMO Used for the Large-scale Data;
针对大规模样本集的SMO训练策略
18.
BP Algorithm Improvement Based on Sample Expected Training Number
基于样本期望训练数的BP神经网络改进研究