statistical pattern recognition造句
例句與造句
- A color image segmentation method for plant disease diagnose based on statistical pattern recognition
基于統(tǒng)計(jì)模式識(shí)別的植物病害彩色圖像分割方法 - Now , the main stream of the technology of speech recognition is based on statistical pattern recognition
目前主流的語(yǔ)音識(shí)別技術(shù)是基于統(tǒng)計(jì)模式識(shí)別的基本理論。 - Application of statistical pattern recognition to the classification of water quality and the recommendation of water treatment reagent prescriptions
統(tǒng)計(jì)模式識(shí)別在水質(zhì)分類和水處理劑配方推薦中的應(yīng)用 - 24 jain a k , duin r p w , mao j . statistical pattern recognition : areview . ieee transactions on pattern analysis and machineintelligence , january 2000 , 22 : 4 - 38
測(cè)試結(jié)果顯示，經(jīng)組合分類器識(shí)別和后處理分析后，系統(tǒng)識(shí)別率達(dá)96 % ，比各單一分類器識(shí)別結(jié)果平均高出4個(gè)百分點(diǎn)。 - In the article , a self - learning stochastic method based on the statistical pattern recognition is presented for attitude control under the disturbance of blind mixed gaussian white noises
摘要本文提出一種基于統(tǒng)計(jì)模式識(shí)別，針對(duì)盲混合高斯白噪聲干擾下衛(wèi)星姿態(tài)控制的方法。 - It's difficult to find statistical pattern recognition in a sentence. 用statistical pattern recognition造句挺難的
- Experiments proved its efficiency and robustness . this recognition system introduced d - s inference theory in statistical pattern recognition , and implemented it by neural network
該系統(tǒng)充分結(jié)合了d ? s證據(jù)理論在不確定性推理方面的優(yōu)勢(shì)以及神經(jīng)網(wǎng)絡(luò)強(qiáng)大的非線性處理能力，實(shí)驗(yàn)結(jié)果表明了這一形狀識(shí)別系統(tǒng)的有效性。 - Statistical pattern recognition methods have been successfully applied to many object recognition problems . one typical example is face recognition , which is the one of the most important fields in patt6rn recognition
統(tǒng)計(jì)模式識(shí)別方法已經(jīng)成功地應(yīng)用到很多目標(biāo)識(shí)別問(wèn)題中，一個(gè)經(jīng)典的例子就是人臉識(shí)別，這是模式識(shí)別領(lǐng)域的一個(gè)重要研究方向。 - Classifier is an important ingredient in pattern recognition . among all the classifiers , linear classifiers are paid great attention in statistical pattern recognition due to their simplicity and easy expansibility to nonlinear classifiers
在模式識(shí)別系統(tǒng)中,分類器是一個(gè)重要的組成部分,分類器設(shè)計(jì)的好壞將直接影響模式識(shí)別系統(tǒng)最終的識(shí)別性能。 - A survey of character recognition methods is presented in chapter 3 . comparison of some extracted feature matching algorithms based on statistical pattern recognition is conducted . these features are profile , mesh and projection of micro structure for distinguishing similar characters
作者對(duì)車牌漢字識(shí)別的特征提取方法進(jìn)行了研究，首先比較了多種基于統(tǒng)計(jì)模式識(shí)別的特征提取匹配算法，包括外圍面積特征，網(wǎng)格特征和用于區(qū)分相似漢字的微結(jié)構(gòu)投影特征。 - In statistical pattern recognition algorithm , the system makes geometry and grey standardize on the images located , then extracts their features base on three kinds of integration projection curve . at last matches them with the feature samples in sample library and output the most suitable image
在人臉的統(tǒng)計(jì)識(shí)別算法中，系統(tǒng)對(duì)定位后的人臉圖像做幾何標(biāo)準(zhǔn)化與灰度標(biāo)準(zhǔn)化處理，并基于三類積分投影曲線抽取人臉特征，與樣本庫(kù)中的特征樣本進(jìn)行匹配，選取最為匹配的人臉圖像作為輸出。 - In theory , based on the characteristic detection probability model of sar image , the ability of distinguishing two connected resolution unit and detecting point target is discussed firstly . then we do conclude that the high precision classification algorithms can build up based on pixel level , which combine three characteristics : the main characteristic ( the rcs statistical distribution ) , two assistant characteristics ( the shadow and structure model ) . secondly , the practical problems of the three pattern classification technologies ( statistical pattern recognition , neural network , fuzzy neural network ) for the sar image are analyzed
在此基礎(chǔ)上，結(jié)合sar圖像其它固有特性研究，提出了以rcs的統(tǒng)計(jì)分布特性作為主要特征，陰影和高分辨率條件下的區(qū)域結(jié)構(gòu)特征作為提高分類精度的輔助特征，并將二者有機(jī)結(jié)合起來(lái)進(jìn)行分類方法研究的思路；分析了統(tǒng)計(jì)模式識(shí)別、神經(jīng)網(wǎng)絡(luò)和模糊技術(shù)應(yīng)用到sar圖像地物分類中需要解決的實(shí)際問(wèn)題；提出了在圖像域?qū)ar圖像質(zhì)量指標(biāo)近似計(jì)算和分類率的具體評(píng)估方法。