machine recognition 中文意思是什麼

machine recognition 解釋
機器識別
  • machine : n 1 機（器），機械；機關，機構。2 印刷機器；縫紉機；打字機；汽車；自行車；三輪車；飛機；〈美俚〉...
  • recognition : n. 1. 認識；識出；識別；面熟，認得；招呼。2. 承認，認可。3. 褒獎，表揚；感謝，酬勞。
  1. One of us ( shapiro ) began this research with the realization that the basic operations of certain biomolecular machines within living cells ? recognition of molecular building blocks, cleavage and ligation of biopolymer molecules, and movement along a polymer ? could all be used, in principle, to construct a universal computer based on turing ' s conceptual machine

    這項研究的開端，是本文作者之一夏比洛意識到，細胞內某些生物分子組件的基本運作方式，像是辨認基本分子建構單元、切開和連接生物聚合分子，以及組件沿著聚合分子移動的方式，理論上都能以塗林的概念為基礎，建構普適的計算器器。
  2. Micr ocr optical character recognition - method of coding machine readable characters micr and ocr for information processing

    光學字元識別.第3部分:信息處理用機讀字元
  3. It have gland - open pump, non - htrottling - process pump, gear pump, cross impeller pump, tilted tray pump ; the four head neck - shrinking and edge - upturned machine, automatism pot - body three shrink neck cross border machine, shrink neck envelop pot assembled machine, envelop pot assembled machine, beat code machine ; glaze machine, press light machine, duplicate membrane machine, etc. product move off sugar - refinery, food can beverage, pack make pot, petrochemicals, printing, etc. court immensity user recognition and trust. welcome to use, wholeheartedly serve

    有開蓋泵無阻塞泵輪泵十字葉泵斜盤泵四頭縮頸翻邊機自動罐身三縮頸翻邊機縮頸封罐組合機封罐機打碼機上光機壓光機，復膜機等。
  4. Knowledge discovery in databases ( kdd ) is a multidisciplinary field, drawing work from areas including database technology, artificial intelligence, machine learning, statistics, neural networks, and pattern recognition

    數據庫中的知識發現（ knowledgediscoveryindatabases ， kdd ）是當前涉及人工智慧、數據庫等學科的一門非常活躍的研究領域。
  5. Chapter 2 has systematically discussed machine learning problem, which is the basic of svm, with statistical learning theory or slt. secondly, chapter 3 has educed the optimal hyperplane from pattern recognition

    第二章探討了支持向量機理論基礎? ?學習問題，尤其是對vapnik等人的統計學習理論（ slt ）結合學習問題作了系統的闡述。
  6. The design is to simulate the process of human. it can adjust the parameters of illation machine ; adopt different recognition strategies according to different states and circumstances with which the recognition object deals. at the same time, it should consider each recognition performance aim

    該識別器的設計是模仿人識別字元的行為過程，它可以根據識別對象所處的不同狀態和不同環境，調整推理機的參數和採用不同的識別策略以及選擇不同的反饋結構。
  7. 13 rivlin e, weiss i. local invariants for recognition. ieee trans. pattern analysis and machine intelligence, 1995, 17 : 226 - 238

    本文的主要貢獻包括以下幾點：第一，提出了一種一致的特徵匹配方法以獲得可靠的對應點估計。
  8. Phrase recognition and analysis in english chinese machine translation

    英漢翻譯中短語的識別與分析
  9. One class classification is a machine learning approach different from the traditional pattern recognition approach where two or more class samples are required. however in some real - life cases, we can hardly, even not, get the samples of some classes, or have to pay costly price to obtain the so - needed samples, such as in the case of machinery malfunction. and while in other cases, the sizes of samples among classes are imbalance, such as medical diagnosis

    單類分類器是不同於傳統模式識別的一種機器學習方法，傳統模式識別方法一般需要多個類別的樣本（至少兩個） ，而在有些場合中，幾乎無法獲取多類的樣本，或者獲取其樣本所需花費的代價非常高，比如：機器故障中我們不可能為了去獲得故障樣本而讓機器特意產生故障；又有些場合的類別樣本個數嚴重不平衡，比如醫學上的疾病特徵與非疾病特徵的比例是嚴重不平衡的。
  10. By mapping input data into a high dimensional characteristic space in which an optimal separating hyperplane is built, svm presents a lot of advantages for resolving the small samples, nonlinear and high dimensional pattern recognition, as well as other machine - learning problems such as function fitting

    Svm的基本思想是通過非線性變換將輸入空間變換到一個高維空間，然後在這個新的空間中求取最優分類超平面。它在解決小樣本、非線性及高維模式識別問題中表現出許多特有的優勢，並能夠推廣應用到函數擬合等其他機器學習問題中。
  11. Most knowledge discovery or data mining tools and techniques are based on statistics, machine learning, pattern recognition or artificial neural networks

    大多數的知識發現或數據挖掘工具和技術是基於傳統的統計、機器學習、模式識別或人工神經網路。
  12. Recognition system of using support vector machine

    基於支持向量機的手寫體數字識別
  13. Named entity recognition ( ner ) technologies have become a hot problem of natural language process recently. the definition of named entity by muc ( message understanding conference ) is the proper nouns and the quantifiers that people are interested in. ner can be classified to person - name, location, organization, date, number and so on. ner has been applied on many compute linguistics tasts as a subtask of information extraction, such as machine translation

    命名實體識別是目前自然語言處理研究的熱點問題。 muc （ messageunderstandingconferences ）對命名實體的定義是:人們感興趣的專有名詞和特定的數量詞，它一般可分為:人名、地名、組織機構名、日期等類型。
  14. This thesis studies the support vector machine and multi - class classification in the statistical learning theory, and applies the support vector machine into the machine paper currency recognition

    本文主要研究了統計學習理論中支持向量機的二次優化演算法和多值分類，並將支持向量機應用於貨幣的機器識別中。
  15. Not only the petroleum geology principle and the concrete handle details of oil field work can not be left in the establishment of whole system, but also the basis of machine cognition that is computer pattern recognition technology

    整個系統的建立既離不開石油地質學原理和油田工作的具體處理細節，也離不開機器識別的依據?計算機模式識別技術。油田沉積相模式識別系統體現了油田開發工作與計算機技術的充分結合。
  16. Character recognition machine

    電碼組合識別機
  17. Usage of real - time image recognition technology in surface mount components taping machine

    實時圖像識別技術在片式元件編帶機中的運用
  18. Iris recognition based on support vector machine

    基於支持向量機的虹膜識別方法
  19. The paper take email the one kind of common digital information mediums as the research object. it realizes the intelligent processing of the mail digital information through the research of mail digital information processing based on machine learning. it enhances the classification and recognition accuracy of the mail digital information in order to satisfy the request that the mail gateway accurately filters the spam mail

    本文以電子郵件這種常見的數字信息媒介為研究對象，通過基於機器學習的郵件數字信息處理技術研究，實現對郵件數字信息的智能處理，提高郵件數字信息分類識別的準確性，以滿足郵件網關對垃圾郵件準確過濾的要求。
  20. The mechanism on machine color vision as well as the relative theory and the application of machine vision in color target recognition are summarized in this thesis. many problems on the machine recognition theory and the system implementation for segmentation are studied deeply and systematically. some new methods for color segmenting, target recognition and tracking, shape extracting are proposed

    本文針對彩色目標的圖像分割和自動識別理論和系統實現中的一些問題開展了較為系統的討論、研究工作，總結提出了幾個解決彩色目標識別中關於色彩分割、目標識別與跟蹤和特徵提取等關鍵性問題的方法與技術，實現了基於機器人的彩色目標識別與跟蹤系統，並完成了相應的實驗。
分享友人
分享到 Line

分享到臉書