This paper presented a new multi-template character recognition method based on principal component analysis(PCA).
本文提出了一种基于主元分析法（PCA）的多模板字符识别算法。
This paper investigates the segmentation of multi-target image based on SVM approach combining feature extraction of kernel PCA.
实验结果表明，结合核主成份分析的特征提取，支持向量机方法是一种很有前景的多目标图像分割技术。
Considering gateway "hot spots" and link loads, this thesis proposes a multi-channel MAC protocol with link priority-aware channel assignment (PCA-MMAC).
考虑到网关“热点”问题和链路负载不均衡，本文提出一种基于链路优先级信道分配的多信道MAC协议(PC A - MMAC)。
Considering gateway "hot spots" and link loads, this thesis proposes a multi-channel MAC protocol with link priority-aware channel assignment (PCA-MMAC).
考虑到网关“热点”问题和链路负载不均衡，本文提出一种基于链路优先级信道分配的多信道MAC协议(PC A - MMAC)。
应用推荐