模式特徵提取 的英文怎麼說

中文拼音 [móshìtèzhǐdīqǔ]
模式特徵提取 英文
pattern feature extraction
  • 模 : 模名詞1. （模子） mould; pattern; matrix 2. （姓氏） a surname
  • 式 : 名詞1 （樣式） type; style 2 （格式） pattern; form 3 （儀式; 典禮） ceremony; ritual 4 （自然科...
  • 特 : Ⅰ形容詞（特殊; 超出一般） particular; special; exceptional; unusual Ⅱ副詞1 （特別） especially; v...
  • 徵 : 名詞[音樂] （古代五音之一 相當于簡譜的「5」） a note of the ancient chinese five tone scale corre...
  • 提 : 提動詞（垂手拿著） carry （in one's hand with the arm down）
  • 取 : Ⅰ動詞1 （拿到身邊） take; get; fetch 2 （得到; 招致） aim at; seek 3 （採取; 選取） adopt; assume...
  • 模式 : model; mode; pattern; type; schema
  • 特徵 : characteristic; feature; properties; aspect; trait
  • 提取 : 1. （取出） draw; pick up; collect 2. （提煉） extract; abstract; recover
  1. In this paper, combined them, automat ic recognize was accomplished successfully through on the image fromgcd

    本論文以ccd圖像為對象在模式識別和特徵提取方面進行了深入的研究，取得了一些成果。
  2. The process of feature extraction is to transform the eradiate noise signal to different feature space and extract the feature vectors that reflect the category of the input sample. the extracted features are the input modes to the classifier

    特徵提取的過程是把輸入的船舶輻射噪聲信號變換到不同的特徵空間，提取出反映樣本的類別特性的特徵向量，並把其作為分類器的輸入模式。
  3. Firstly the patterns of the multifingered hands are detailed, eight patterns are defined. the classical bayes method is used in the classification of pre - grasp of multiple fingers based on three patterns which are grasping, holding and pinching. based on the eight pre - grasp patterns, bp neural network is applied in the classification of the pre - grasp of multifingered hands and gets a good effect. the method solves the shortcoming input sample relying on the propobility density and simplified the un - insititution characters extraction. in this paper, support vector machine ( svm ) and binary - tree with clustering is applied in the classification. this method can solve the slow speed and effect with fewness sample in the classification, achieving a good effect. in this papper, we extract the characters of the regulation object with geometry characters and extact the unregulation object with the image analysis

    此法解決了輸入樣本依賴物體的概率密度的特點，簡化了分類特徵提取的不直觀性。本文還採用了支持向量機（ svm ）和聚類二叉樹相結合的方法對機器人手預抓取八類模式進行分類，解決了預抓取模式分類訓練速度過慢以及在分類中樣本數量偏少而影響分類效果的問題，得到了較高的正確率。本文對預抓取幾何形狀規則的物體採用直接提取其幾何特徵，對于預抓取幾何形狀不規則的物體採用圖像分析的方法進行特徵提取。
  4. In the phase of image pretreatment, the main jobs of this system includes dot operation, image swell, positive chiasma transform, edge extraction and edge swell, outline track, etc. because the visual system itself is a neural system, systematizer designed in the paper adopts bp neural network to accomplish computer image identification, the system has some advantages over the traditional one, but with the extensive application of bp neural network, the problems existing in bp neural network come forth increasingly

    在系統軟體設計部分中，首先是對所選零件進行模式識別，包括圖像預處理、特徵提取和分類器設計三個階段，其中在圖像預處理階段本系統主要做的工作有：點運算、圖像增強、正交變換、邊緣提取和邊緣增強、輪廓跟蹤等。由於視覺系統本身就是一個神經系統，故本文所設計的分類器採用bp神經網路，其具有一些傳統技術所沒有的優點。
  5. The basic theories applied to this project are researched and the key techniques of carrier calculation, characters counting, and mode recognition are described. because there are many practical problems involved in the project, the method of evaluation and the evaluation are given by engineering rule

    本文對涉及的基本理論在系統中的應用進行了研究並對其中的載頻計算、特徵提取和模式識別等關鍵技術進行了闡述。系統性能的評價涉及到大量的實際問題，本文從工程角度給出了評價方式和評價結果，體現了系統的特色。
  6. This paper, based on normalizing well logging data while drilling and correcting depth into true vertical depth and calculating reservoir parameters and etc, combining the practical ease of mobei oilfield, extracted logging and geological pattern characteristic of target oil - gas formation and geosteering mark formation, and used bp neural network and regressive analysis to create predicting mode of geosteering parameter to build relevant contrast curve ; adopted geometry geosteering method to fix on die drilling direction of bit upper and declination, the position in reservoir, to judge the real drilling case. all finely solved the problem to follow the geological target while drilling for three horizontal well these methods improve the drilling horizontal well ability by using the techniques to follow the geological target while drilling, and then it is convenient and practicable

    本文在開展隨鉆測井資料的標準化和斜井校正及儲層參數解釋與含流體性質判釋等工作的基礎上，結合研究工區莫北油田的實際情況，提取了目標油（氣）層和導向標志層的測井地質模式特徵，並採用bp神經網路法和回歸分析法建立了地質導向參數的預測模型、構造了相應的對比曲線；採用幾何導向法確定鉆頭上下傾鉆進方向及其在目標層的位置，以判斷實際鉆進地層情況，很好地解決了研究工區三口水平井的隨鉆跟蹤地質目標的問題。
  7. In order to deal with the unknown transformations of samples as a result of preprocessing and improve the system recognition performance further, a palmprint feature extraction method based on template learning in wavelet domain is designed and proposed. this algorithm learns the ideal templates of different classes from palmprint samples, whose parameters are regarded as

    該演算法從掌紋樣本中學習不同類別的理想模板，並將理想模板的參數作為特徵用於模式分類，由於考慮了子圖樣本內在存在的平移和旋轉變換，不同類型小波系數對特徵提取的貢獻，因此達到非常好的識別效果。
  8. After an introduction to the concept and property of the wavelet and present applications in communications, this dissertation focuses the research on the wavelet ' s application to extraction and analysis of the fine features of typical communication signals, and four problems are discussed : ( 1 ) an new method for the feature extraction and pattern recognition of typical communication signals a distinct method based on wavelet transform is proposed

    本文在簡要回顧了傳統小波的定義、性質、發展歷史和目前小波在通信領域中的應用后，著重研究小波在典型通信信號細微特徵提取與分析方面的應用，主要研究工作和研究結果集中在四個方面： （ 1 ）典型通信信號特徵提取與模式識別的新方法。通信信號的特徵提取與模式識別在通信對抗領域有著重要應用。
  9. In this paper, we treat the puzzle for gene mapping as a pattern recognition problem and propose a feature selection algorithm ( mpisc ) to mine snp combination remarkably associated with complex trait. this method offers us a new way for gene mapping from a global view

    本文中的研究中，我們將基因定位問題看作提取疾病特徵標記（比如snps ）的模式識別問題，提出了snp協作簇的特徵提取演算法mpisc ，這里我們稱一組相互作用的snps為一個協作簇。
  10. In this paper we studied the textural features extraction, remote sensing images classification and bp neural network techniques and their applications in the meteorological problems such as recognition of the cloud cluster feature, cloud - drift wind retrieval and heavy rain process analysis etc. to the question of the low precise recognition of satellite images by using spectral features, the proposed approach assumes to perform a multiple analysis based on an advisable decision - making model by first developing a mixed pixel model which was based on the textural features of images, and then improving the recognition intelligence

    本文對模式識別領域中的圖像紋理特徵提取、遙感圖像分類、 bp神經網路與紋理特徵組合分類等方法，以及它們在雲團屬性識別、雲跡風反演和暴雨過程分析等氣象問題中的應用作了研究。針對過去利用圖像光譜亮度特徵進行識別分析氣象衛星圖像準確度不高的問題，本文提出了發展混合像元的分解模型，以圖像的紋理特徵為基礎，提高圖像識別的智能水平，以實現在分析決策模型的支持下，快速準確的復合分析的解決方案。
  11. Pca & flda ), knowledge - based methods and neural - networks based methods, etc. in this thesis two novel classes of feature extraction methods are proposed, i. e. matrix - pattern - based and vector subpattern - based representation methods respectively

    在本文中，我們在pca和flda方法的基礎上提出了兩類特徵提取新方法，即基於矩陣模式和基於子向量的特徵提取方法，並隨後用于模式的分類。
  12. This type of strategy has two main shortcomings : 1 ) useful information for classification task contained in the matrix structure may be jeopardized in the vectorizing procedure ; 2 ) after vectorizing procedure computation complexity in classification task may increase substantially due to the vector pattern representation

    這種方法存在著兩個主要的缺點： 1 ）矩陣模式中對分類有用的結構信息很可能會因為向量化的操作而遭到破壞； 2 ）向量化的操作極大的增加了特徵提取及隨后識別的運算復雜度。
  13. In this paper, inspired by the method of feature extraction directly based on matrix patterns and the advantage of mhks, we develop a new mhks classifier based on matrix patterns ( matmhks ). the method can mitigate the above shortcomings. we also make a further try of applying the algorithm proposed above to breast cancer detection

    受到已有面向矩陣的特徵提取方法的啟發，本文將此方法引入到正則化h - k線性分類器的設計中，設計出面向矩陣模式的雙邊正則化h - k分類演算法matmhks ，克服了以上不足，並繼承了mhks演算法的優點。
  14. Currently, image recognition has five primary methods : classical statistic model method, auto method based on information, auto method based on model, amalgamation of several sensors and manual neural network. how to improve the classical method and how to assemble different recognition method are still problems to be improved. based on the current research state, the classical statistic model recognition method and correlative knowledge are researched firstly

    基於當前的研究現狀，本文以可見光和紅外儀器同步拍攝的不同環境下的運動車輛目標序列為對象，在深入研究了經典的統計模式識別方法及相關理論的基礎上，對車輛目標識別系統中的特徵提取和識別方法等方面做了較深入的研究，並對神經網路在車型識別系統中的應用作了試探性研究。
  15. The other one is the synthetical local nonlinear pca neural network recognition model constructed by combining the nonlinear generalization of pca and sub - space pattern recognition technology. we use the two recognition systems in handwritten digitals and characters recognition and obtain some satisfactory results. compared with some traditional classifiers, our systems have better recognition performances

    而基於非線性pca的神經網路識別模型對傳統的線性pca進行了推廣，並利用了子空間的模式識別方法，針對每個字元類使用神經網路建立多個模板，然後利用pca神經網路和聚類演算法構造自動編碼器組對模式類進行重構，避免了特徵提取的復雜性和信息的丟失，提高了系統的識別性能和運算效率。
  16. We designed and made the attraction device to attract agricultural pests, obtained agricultural pests " images with the color camera, processed images based on wavelet analysis. on the basis of these, we emphasized on extracting effective features, put forward recognizing pests " classes with pests " colors and texture features, and succeeded in extracting five efficient features such as color features, wave image edge moments features and so on. then we selected features, inputted into neural network classifier, recognized pattern, presented detection results

    本文設計製作了誘捕裝置，誘集農田害蟲，使用攝像頭攝取害蟲圖像，採用小波分析進行圖像處理，在此基礎上重點進行了特徵提取工作，提出了利用害蟲顏色和紋理等特徵進行種類識別的觀點，並成功提取了彩色特徵、小波圖像邊緣矩特徵等五類有效特徵，並經特徵選擇后輸入神經網路分類器進行模式識別，最後給出檢測結果。
  17. Applied in license plate segmentation problem, a new segmentation method of automobile license plate based on wavelet transform and neural network is pointed out [ 71 ]. 2 ) phase of image feature extraction : combined with the feature extraction of structural and statistical method, a method of image character feature extraction based on wavelet and moments analysis is presented [ 74j. 3 ) phase of image classificaton [ 73 ] : after investigation on intelligence recognition technology, the paper puts forward basic structure of recognition machine ' s model, and makes a primary research of basic structure and design method, then makes research of the multi - character method

    並應用於車牌分割問題，提出基於小波與神經元模式識別的車牌圖像分割方法； 2 ）特徵提取階段：將結構特徵提取方法和統計特徵提取方法的緊密有機結合，提出一種基於小波和矩的車牌圖像字元特徵向量提取方法； 3 ）分類識別階段：對智能識別技術進行研究，提出智能識別機的模型結構，對識別機的基本層次結構和設計方法進行初探；並針對多特徵方法進行一定的研究；本文提出的基於模式識別的圖像處理方法對其他領域的圖像處理具有一定的參考價值。
  18. The feature extraction and pattern recognition are introduced in structural damage identification

    研究了結構損傷識別中的特徵提取和模式分類方法。
  19. In this article, pattern recognition is used as theory foundation and image process technology as basic technology. combining with the new theory tools ( wavelet analysis and neural network ), this paper presents effective resolve methods to three parts of image recognition ( image segmentation, image feature extraction and image classificaton ) thought systemic analysis of it

    文中以模式識別為基本理論平臺，以圖像處理技術為基本手段，結合新興領域的理論工具（小波分析，神經網路等） ，分別對圖像分割，圖像特徵提取，圖像分類識別三個問題作了系統研究，並提出了有效的解決方法。
  20. That is of our interest and is explored in the thesis ' s second part. we proposed sppca & spflda feature extraction methods. contrary to matpca & matflda, they follow a first - partition - then - extraction procedure

    在本文的后一部分，我們就對此進行了研究，提出了具有先分解后提取過程的基於向量子模式特徵提取的方法（ sppca和spflda ） 。
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