harr 中文意思是什麼
harr
解釋
哈爾-
Harr potter : bertie bott ' s every flavor beans
哈利?波特：比比多味豆？ -
In chapter 5, the algorithm theory of the mrtd method is discussed, and the deduce of mrtd is consummated and the frame of mrtd is constructed. and this chapter deduces the detailed formula using battle - lemarie wavelets and harr wavelets, respectively
接著第五章討論了mrtd的理論原理，補充和完善了mrtd的推導，構建了mrtd的基本框架，並分別以battle - lemarie小波和harr小波為例推導了詳盡的迭代公式。 -
In the final, the thesis build a rapid face detection system using a cascaded classifiers based on adaboost learning algorithm, harr - like feature and the method of building classifier
最後本文運用基於adaboost學習演算法和harr - like特徵及本文提出的由特徵構造分類器方法，採用一種分級分類器的結構，搭建了一個快速的人臉檢測系統。 -
On the basis of the stresses analysis, the existed design rules of pressure tunnels are discussed. first, the pore - water - pressure distribution in the rock mass around the pressure tunnel is evaluated using the image well method proposed by harr ( 1962 ). the seepage - induced stresses in the rock mass is analyzed, and several conclusions are gained
首先，運用harr （ 1962 ）鏡像原理推求壓力隧洞圍巖中水壓力分佈；結合水壓力的分析，利用fernandez （ 1994 ）的假定推求壓力隧洞圍巖中滲流產生的應力場，並對不同地表條件下滲流產生的應力場進行詳細分析，從中得到一些結論。 -
The thesis discussed respectively these three factors in the rapid detecting algorithm based on learning, studied emphatically the method of building classier based on features and the combing of the weak classifiers which is needed to build rapid face detection system. about building classifier based on harr - like features, the thesis put forward a novel method based on the symmetry efface
本文對基於學習的檢測演算法中的三個要素分別展開了討論，重點研究了由特徵構建分類器的方法和構建快速人臉檢測系統所必需的弱分類器的組合，關于特徵構建分類器，提出了一種新的基於人臉對稱性的由特徵構造分類器的方法。 -
The 1 - dimension was decomposed by harr wavelet in depth of 2 - layer, then we could construct a characteristic information from the low frequency part of the wavelet coefficients and compare it with the corresponding information of the standard characters, this led to a rapid and efficient character recognition. the total experimental character recognition rate was above 92 %
將投影得到數據進行2層小波分解，從其中各層平滑分量提取一個特徵信息，將其與模板字元對應的特徵信息進行分析比較，實現了字元的快速高效識別，識別率達到92以上。
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