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一种简单有效的基于动态时变语音识别源码
对于大多数研究者来说,寻找能够匹配二重时间序列信号的最佳途径是很重要的,因为它有许多重要的应用需求.DTW是实现这项工作的显著技术,尤其在语音识别技术领域,在这里一个测试信号被按照参照模板拉伸或压缩,
,Searching for the best path that matches two time-series signals is the main task for many researchers, because of its importa
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基于模板匹配算法的识别技术，对输入的手写字符能进行实时的识别。-Recognition algorithm based on template matching techniques can input handwritten character recognition in real time.
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Experimental results on Bern face database and our 350
subjects database show that our method makes impressive
performance improvement compared with the
conventional Eigenfaces and template matching techniques.
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This algorithm is designed to segment an satellite image using Kmeans, and then all kmeans clusters Satellite image (target image) and template image using local binary pattern (LBP) and then applied various template matching techniques between LBP K
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In this paper, we extend Fisherface for face recognition
from one example image per son. Fisherface is one of
the most successful face recognition methods. However,
Fisherface requires several training images for each face,
so it cannot be ap
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