特徵提取 的英文怎麼說

中文拼音 [tèzhǐdīqǔ]
特徵提取 英文
feature extraction
  • 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...
  • 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 automated extraction of catchment properties from digital elevation models

    的流域特徵提取綜述
  3. Extracting terrain features from contour maps based on united - delaunay - triangulation model

    三角網的等高線地形特徵提取研究
  4. Extracting topographic structure from dem and application

    的流域特徵提取及應用
  5. Application of multiresolutional filter on feature extraction of palm - dorsa vein patterns

    多解析度濾波在手背血管特徵提取中的應用
  6. Feature extraction of eeg based on grey system theory

    基於灰色系統理論的腦電特徵提取
  7. Characterization of waste - analysis of eluates - determination of ammonium, aox, conductivity, hg, phenol index, toc, easily liberatable cn -, f -

    廢棄物特徵.提取物分析.銨aox傳導性汞苯酚指數toc和易析出的cn f的測定
  8. At last, i conclude a way to increase the recognition ratio of the under - water target. the method of this dissertation is to distinguish the property of the under - water target by eradiate noise

    主要的工作是在前期研究的基礎上，利用已有水中目標的特徵提取和識別方法，應用人工神經網路技術，總結出一種水下目標識別方法。
  9. 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。
  10. Through the inspecting, the author selected three methods of eradiate noise ' s feature extraction. the methods include the pedigree, e - filter, fractal. in those methods, the pedigree is based on frequency field, the e - filter is based on the energy field and the fractal is based on time field

    本文作者經過考察，採用了三種前期研究中較為有效的水下目標特徵提取方法? ?基於功率譜估計的線譜特徵提取方法、基於小波分析的不同頻段內能量特徵提取方法和基於水聲信號分維特性的特徵提取方法。
  11. We excogitate the gabor filter based - on sub - block texture analyse to extract the feature of iris normalized image and encode them. then, we use hamming distance to match two iris codes. in order to reduce the rotation of iris, we work out a new method

    4 .研究出基於子塊紋理分析的gabor濾波器方法來對虹膜歸一化圖像進行特徵提取和編碼;在虹膜編碼匹配中，本論文採用hamming距離來進行編碼之間的匹配。
  12. On character extraction, the thesis regards handwriting images as texture images, and excogitates analyzing handwriting images with ( 2, 10 ) integer - to - integer wavelet transform innovatively, that is, analyzing texture images with ( 2, 10 ) integer - to - integer wavelet transform mainly, and denoting eigenvectors of handwriting images with integer - to - integer wavelet coefficients, the thesis defines an 18 - dimension eigenvector. ( 2, 10 ) integer - to - integer wavelet transform can extract the high pass of images effectively, high pass is the details of images, and analysis of texture images is mainly for the details

    在筆跡圖像的特徵提取上，文章把筆跡圖像當作紋理圖像來看待，創新地提出用（ 2 ， 10 ）整數小波變換來分析筆跡圖像，即主要用（ 2 ， 10 ）整數小波變換分析紋理圖像，用紋理圖像的整數小波系數來表徵筆跡圖像的特徵向量，文章定義了一個18維的特徵向量。 （ 2 ， 10 ）整數小波變換能夠很好地提取圖像的高頻部分，高頻部分在圖像中表現為細節，而對紋理圖像的分析主要是對細節的分析。
  13. 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。
  14. The characteristic of power quality signal ' s deal by wavelet multi - resolution decomposition and time - domain analysis is studied then brings forward combine the tow methods and uses it to filter bed yawp, decomposition and feature extraction. 8 kinds of power quality are classified and characterization of sag is specially classified

    然後研究了小波多解析度分解和時域分析電能質量信號處理的特點，提出了應用兩種方法相結合的方法，對電能質量信號進行去噪、分解，通過大量的計算機模擬工作，對擾動信號進行了特徵提取。
  15. Using the way combining the mathematic morphology top - hat and gauss matched filtering can effectively reduce the influence of the inherent fovea and the marginal noise brought forth by the retinal camera caliber in retinal image and increase the precision of retinal image segmentation and feature point extraction

    文中提出了採用灰度數學形態學中的top - hat變換和高斯匹配濾波相結合的方法，用來有效的降低視網膜熒光圖像中固有的小窩現象及眼底照相機的口徑所引起的視網膜圖像邊界像素噪聲，極大的提高了圖像分割及特徵提取的精度。
  16. In this paper, we made an investigation into texture feature extraction and classification based on statistic method and its application in multi - spectral image classification. the research works of this paper have been done as follows : firstly, in order to overcome the weakness of gray level co - occurrence matrix ( glcm ), a new unsupervised texture segment algorithm, based on multi - resolution model, is presented in this thesis

    本文主要研究了基於紋理統計特性的特徵提取與分割方法，並將其用於實際的多光譜圖像分類，具體工作如下:第一，針對傳統灰度共現陣方法中特徵提取的尺度單一問題，本文提出了一種多分辨無監督紋理分割演算法。
  17. Optical implementation of haar edge wavelet and extraction of image feature

    子波的光學實現及圖像邊特徵提取
  18. 6 an algorithm of kurtosis signal - to - noise ratio ( ksnr ) based the mot - radiated noise polyspectrum feature extraction is presented

    6提出了基於峰度信噪比的水下h標輻射噪聲的多譜特徵提取演算法。
  19. The efficiency and reliability of minerogenetic prediction can be improved by combining rs with gis. we processed rs images, extracted the geological information related to mineralizing, such as geology, structures, stratam, rocks, etc, synthetically analysed remote sensing, the geological data and geo - chemistry, under the guidance of the theory and mathematic model, set up gis mineralize model. on this condition, to develop this method and its theory, and to establish a system of perfect prediction, it is not only useful in studied degree area but also favorable for looking for new type and some form large - scale deposits in old studied area, and it has a great theoretical meaning

    遙感與gis相結合用於成礦預測中可大大提高預測工作的效率和可靠性。通過對研究區的遙感圖像處理和地質、構造、地層、巖石、礦化蝕變等有關信息的特徵提取、遙感、地質數據和物化探數據的綜合與復合分析，在一定成礦理論和數學模型指導下，建立gis綜合找礦模型。在此基礎上，發展這一方法及理論並建立完善的預測體系，不僅對研究程度較低的新區礦床預測有用，而且對研究程度較高的老區尋找新類型和點狀大型、超大型礦床都具有重要理論意義和實際意義。
  20. Fingerprint image feature extraction mainly extracts the minutiae and their positions

    指紋圖像的特徵提取主要是提取指紋的細節特徵及其位置。
分享友人
分享到 Line

分享到臉書