目標的特徵 的英文怎麼說

中文拼音 [mùbiāodetèzhǐ]
目標的特徵 英文
clarification of objective
  • 目 : Ⅰ名詞1 （眼睛） eye 2 （大項中再分的小項） item 3 [生物學] （把同一綱的生物按彼此相似的特徵分為幾...
  • 標 : Ⅰ名詞1 [書面語] （樹梢） treetop; the tip of a tree2 （枝節或表面） symptom; outside appearance; ...
  • 的 : 4次方是 The fourth power of 2 is direction
  • 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...
  • 標的 : aim
  • 特徵 : characteristic; feature; properties; aspect; trait
  1. The second section described the accounting issues brought by cyber economy environment including the impact to the accounting suppose, accounting target, the content, the means, the process of accounting checking and the impact to the accounting information system. the third section described the ideas of the innovation of cyber economy environment emphases on the accounting business process reengineering, accounting information system innovation, assets affirmance, accounting settlement under the cyber economy environment. on basis of the third section, the fourth section analyzed the cyber accounting ' s origins, developme nt, characteristic and problems occurred in the development of the cyber accounting

    本文共分四章，第一章論述了網路經濟環境下會計環境的變遷，分析了網路經濟的產生與特點，概述了電子商務及虛擬企業的特徵，並指出對企業的組織、生產、管理環境帶來的巨大變化；第二章闡述了網路經濟環境引發的會計問題，包括對會計假設、會計目標、會計核算內容、方法、流程及會計信息系統的影響；第三章提出了對網路經濟環境下的會計創新的設想，重點論述了網路經濟環境下的會計業務流程重組與會計信息系統的變革，網路經濟環境下的資產與會計確認，以及會計結算等方面的創新設想；在第三章討論內容的基礎上，第四章具體分析了網路會計的產生、發展及特點，並分析了網路會計發展過程中存在的主要問題，針對這些問題，提出了相應的對策。
  2. Eradiate noise recognition obtains feature information of movement under - water target, which is produced by passivity sonar, and then decides its category by referring to a priori knowledge

    本文的研究方法是從目標產生的輻射噪聲中提取出目標的特徵信息，結合已有的先驗知識，對目標的類別做出判斷。
  3. 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。
  4. A new fractal - based infrared image feature extraction method is presented and the detailed theoretic analysis and implement procedure of this algorithm is submitted and tested in some experiments. with the limitation of the line detection based on traditional hough transform that the information of the length and the end points of the line is unavailable, a new algorithm which makes use of the accessional strategy based on precognition information is put forward to meet the demand for more information of the line, simulation results show this method is effective. finally, the whole process of airport target recognition is presented and the result images are also given

    使用分形方法提取目標的特徵，在知識指導下，提出了一種基於目標特徵模型的降維的形態學分形維數計算方法，對傳統分形方法進行了改進，從理論上推證了演算法的合理性，並對演算法進行了模擬分析；針對傳統hough變換無法獲得線段端點和長度信息的局限性，提出了一種基於目標特徵先驗知識的hough變換融合策略，通過引入目標先驗知識，可以有效地獲得直線信息；對信息多而復雜的機場目標採用基於知識的目標識別方法，使用置信度模摘要型實現不確定推理，對目標進行識別判斷，將知識貫穿于整個識別過程中，對目標進行了有效地識別。
  5. In this dissertation, a gabor wavelet based method is used for tracking a target such as plane and vehicle with bad deformations including rotation, translation, scale and other affine transforms. the study of this method included feature abstraction ; feature tracking and feature refreshing

    本文使用gabor小波特徵提取方法，針對存在旋轉、平移、比例等仿射變化的飛機、車輛等軍事目標，對特徵提取、特徵跟蹤以及特徵更新方法進行了研究。
  6. The system firstly learns the domain training samples by using thesaurus to process word - separation and word - frequency statistics. according to word - frequency distribution, it chooses the feature collection and their weights to formulate feature vector and generate domain model and user model

    系統首先對領域訓練樣本進行學習，利用領域詞典對訓練文本進行詞條切分和詞頻統計，並根據詞頻分佈，提取代表採集目標的特徵項集和相應的權重，生成特徵矢量，形成初始領域模型和用戶模型。
  7. By using both of the two methods, we extract the features of the target images, then we applied the features to the artificial neural networks in the recognition part. we utilize the artificial neural networks method to identify the images in the recognition part. an improved back propagation ( bp ) algorithm was introduced to train the neural network for recognition

    在旋轉不變性和特徵提取方面，研究了目標的zernike不變矩方法，並且提出了用小波分析在目標圖像特徵提取方面的應用，分別用zernike矩和小波分析方法提取了目標的特徵值，將兩者提取的特徵值分別作為目標識別分類器的輸入。
  8. 3 ) using the capability of tms320c5409, all the algorithms of separating a target from its background, extracting the character and identifying the target are operated in " parallel ". for example, during the separation of target from its background the characters of the target were picked up

    利用tms320c5409的特點，將目標分離、特徵提取、目標識別等演算法的操作「并行」進行，如在目標和背景分離的過程中提取目標的特徵量，大幅度提高了系統的運算速度。
  9. At the same time, dominant points is useful for their visual feature stability in feature match. in this paper, we propose a simple dominant points algorithms in the cases where the dominant points are very distinctly

    同時，在圖像輪廓角點特徵比較明顯的情況下，用角點提取技術提取目標的特徵點集，並設計了點集匹配函數，用於目標間的匹配與跟蹤。
  10. Under the situation of engineering, the algorithms for features extraction based on analyzing the characteristics of test range targets are mainly studied

    在此工程背景下，本文嘗試著從靶場目標的特性出發，總結和研究相關姿態特徵的提取方法。
  11. In waveform design aspect the impulse response elimination method is presented to detect and discriminate the targets. in the signature waveform detection aspect the target ' s late - time response is adopted as the signature waveform, then the adaptive beam formation arithmetic is used to detect this signature waveform

    在發射波形設計中提出了沖擊響應消去法，設計與目標匹配的發射波形來檢測和識別目標；在特徵波形檢測中提出用目標沖擊響應的晚期響應作為目標的特徵波形，再利用自適應波束形成的演算法來檢測待測目標的特徵波形。
  12. This paper defines four features of a target based on ir radiation characteristics, the fusion feature was presened after the four features were normalized and weighted

    摘要針對復雜背景下的紅外弱小目標的特徵提取問題，提出了一種實用的紅外目標的特徵量提取演算法。
  13. After researching in image recognition, and according to the characteristics of the moving traffic objects, it introduces the method of recognition based on the characteristics of object moments

    在研究圖象識別的基礎上，根據交通目標移動的特點，引入了基於目標矩特徵的識別方法。
  14. We summarized the identification features, appraisement standards, as well as the target characteristics of the remote sensing images

    全面總結了遙感信息的特點，遙感目標的特性，遙感信息的評價標準以及遙感圖像的識別特徵。
  15. This paper studies the feature extraction of linear objects in remote sensing images and the computer - aided auto - recognition of airports

    本文研究遙感影像線狀目標的特徵提取和機場目標計算機自動識別方法。
  16. Now, the extraction of motion object in dynamic background is a important developing - direction in digital image process, and it is very significative

    當前動態背景中運動目標的處理是數字圖像處理領域中的一個重要發展方向，對于運動目標的特徵提取具有深遠的意義。
  17. To improve the stability of target tracking, we had worked on the follows : ( 1 ) computer simulation technology in active illumination environment. ( 2 ) research of target extract algorithm

    為提高主動照明跟蹤的穩定性，本文就湍流下的主動照明目標的特徵從模擬方法和照明目標特徵提取演算法兩方面展開研究。
  18. Chapter 1 is introduction, represented the advance of study task, automatic recognition technology of cannonball ' s defection include edge detection, feature extraction and pattern recognition, and solving project of the system

    本文的第一章是緒論，闡述了研究課題的提出，對炮彈裝藥自動識別技術包括圖像邊緣檢測技術、目標的特徵提取技術、目標的模式識別技術進行了概述，提出系統的解決方案。
  19. Then the markov random fields ( mrf ) theory was used to segment target df active illumination by light and sobel - transform information in this article. to make mrf algorithm suitable in actual setting, some technologies were analysis to make extracting steady. according to the analysis of laser beam through atmosphere turbulence, we found that : 1

    其次，圍繞目標的特徵提取問題，文中討論了含噪照明目標圖像的分佈特點，並從亮度和邊緣變化方面對照明光束遠場特徵進行了分析和歸納，提出採用基於mrf理論對照明目標分割來提取目標形心特徵的方法。
  20. At the same time, based on the character - selecting principles of recognition and the fact that many important objects in remote sensing images behave linear and the practical need of recognition of these objects, we point out that the edge information represents the image content and raise the method of character extraction and recognition through linear shape

    同時根據目標識別的特徵選擇原則，從遙感影像許多重要目標表現為線性形狀的特點及這些目標識別的實際需求出發，提出了以目標邊緣信息作為反映圖象內容的一個特徵，研究了基於線狀目標的特徵提取和識別的方法。
分享友人
分享到 Line

分享到臉書