pattern recognition 中文意思是什麼
pattern recognition
解釋
程式識別- pattern : n 1 模範，榜樣；典範。2 型，模型；模式；雛型；【冶金】原型。3 花樣；式樣；（服裝裁剪的）紙樣；圖...
- 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。
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Clastic facies pattern recognition is somewhat systematic.
碎屑巖相模式的識別是帶有一定系統性的。 -
In this diploma thesis, the statistic and structural characteristic of musical score image is analyzed and synthesized by relevant technology of image project, pattern recognition, mathematical morphology, software engineering, music knowledge, midi and so on. the concept of direction number has been defined, and then the mathematical morphology theory is used to process musical score image and recognize musical information. specialized direction number algorithms are firstly used to preprocess a musical score image and then recognize stafflines, barlines, pitch, note values, clef, etc. finally the musical information of the musical score image is automatically stored in the midi format
本文利用圖像處理、模式識別、數學形態學、音樂知識庫與midi等相關技術，分析與綜合數字樂譜圖像的統計與結構特徵，提出了方向數等概念，對樂譜圖像進行處理，利用直方圖技術與方向數演算法識別譜線、小節線、符乾等樂譜的主要框架，然後用數學形態學理論識別音高與時值，最後根據這些音樂信息，組合成音樂樂譜信息，並自動轉化成midi格式。 -
Immune evolutionary algorithms are optimal algorithms in essence, therefore, they can be used in some fields, such as cybernation, pattern recognition, optimal design, meshing learning, network security, etc. there are also some examples of these attempts described in this paper
免疫進化計算在本質上講是一種優化演算法，所以它們可以應用於一些諸如自動控制、故障診斷、模式分類、圖象識別、優化設計、機器學習和網路安全性等廣泛領域，本文在這方面也做了一些初步的嘗試。 -
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。 -
3d object recognition across multiple views is an important problem in the flied of computer vision and pattern recognition
摘要多個視角下三維物體的識別一直是計算機視覺和模式識別領域的重要研究方向。 -
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。 -
On the major premise of feasibility of this theory, this article based on the practice of fore - runners, has done some further research work about the application of genetic algorithm for image compression and pattern - recognition with a satisfactory result
基於這個理論可行性的大前提，本文在吸取前人實踐經驗的基礎之上，深入研究了遺傳演算法在圖像壓縮，模式識別兩個問題中的應用策略，並得到了比較滿意的結果。 -
Considering the characters of bp neural network, such as the simple structure, the advisable malleability, self - fitness, self - studying, nonlinear function approximating, the considerable abilities of parallel computing, fault - tolerant and so on, the bp algorithm have been extensively applied to the areas of system modeling, pattern recognition and seismic exploration since 1986. compared with other algorithms, as the above reasons, the bp algorithm has become the most usual and efficient solutions to the artificial neural networks
由於人工神經網路中的bp神經網路結構簡單，可塑性強，具有良好的自適應、自學習、極強的非線性逼近、大規模并行處理和容錯能力等特點，自1986年rumelhart等人提出以來，被廣泛應用於系統建模、模式識別、地震勘探等重要領域。而bp演算法數學意義明確，步驟分明，是神經網路中最為常用、最有效、最活躍的一種方法。 -
Facial representation and recognition is one of the key issues in pattern recognition, computer vision, and image understanding fields. it is widely applied to numerous commercial and law areas, such as mug shots retrieval, real - time video surveillance, security system and so on
人臉的表示和識別技術是模式識別、計算機視覺和圖像理解系統的研究熱點之一，在公安和安全部門有著廣泛的應用，例如搜索罪犯、動態監視、銀行密碼系統等。 -
Abstract : events contributing to the establishment of statistics the science of data and its chemical branch are epitomized. as the new chemical branch named chemometrics or chemstatistics has been disputed in the circles of chemistry for a long time, reasons for adopting chemstatistics are given, which is defined as the science of gathering or generating, describing, summarizing and interpreting the data concerned to acquire new chemical knowledge or information. the fact that many traditional statistical methods, such as significance tests, analysis of variance, regression and correlation, and some others not usually considered statistical, such as model building, monte carlo method, fourier transformation, artificial nerval networks and pattern recognition, each contains one or more of the five connotations of statistics is expounded. the regular pattern that a chemstatistician grows up is approached. the urgent task is to include chemstatistics in the undergraduate or graduate curriculum of chemistry specialty. the goal of the project is to nurture chemists who know statistics
文摘:本文追溯了統計學發展、建立中的大事，陳述了它的定義及其化學分支發展、建立的梗概；鑒于化學界對該新興化學分支學科的名稱長期存在爭議，提出了以化學統計學而不以化學計量學為該學科名稱的理由，把化學統計學定義為一個研究有關數據的收集或產生、描述、分析、綜合和解釋，以獲得新化學知識或信息的學科；闡明了許多公認屬于統計學的方法，如顯著性檢驗、方差分析、回歸和相關，以及一些尚未認定屬于統計學的方法，如模型建立、蒙特卡羅方法、傅立葉變換和人工神經網路，都含有統計學5個內涵中的一個或多個；探討了化學統計學家成長的模式，認為當務之急是把化學統計學納入化學專業的教學計劃，以培養懂統計學的化學家。 -
The detailed works are as follows : the finding patterns problems in the time - series data sequence are described, and a new trend logic expression method is introduced, and its algorithm and experiment result of algorithm are given ; time - scries data are disposed, and using the arctg. slope of line as the sample of pattern recognition, so ignoring the aberrance of pattern in the classified. in addition, a new time - series pattern finding algorithm based on higher - order neural network is put forward
同時給出了本文的具體的工作，主要是：對在時序數據序列中發現模式問題進行了描述，並介紹了一種新的趨勢邏輯表示方法，給出了其演算法及演算法的實驗結果；對時序數據進行處理，提出了利用線段的斜率反正切值作為模式識別的樣本，從而在分類時忽略模式的畸變；另外，還提出了一個新的基於高階神經網路的時序模式發現演算法。 -
A model study of pattern recognition in rhinopithecus roxellanae subspecies
川金絲猴亞種的模式識別模型研究 -
A novel learning algorithm for synergetic pattern recognition
一種新的協同模式識別學習演算法 -
A study on the pattern recognition of thermophilic and mesophilic proteins
嗜熱和常溫蛋白模式識別的研究 -
Texture analysis is a main and useful area of study in pattern recognition
紋理分析是模式識別中一個重要的分支。 -
On the basis of that, the method of acquiring characteristics by infrared plane detection is given, according to the characteristics gained and the pattern recognition, a fuzzy - neural vehicle classifier based on the vehicle ' s length height and axles is carried out
採用二維紅外檢測技術獲取車輛外形幾何參數的方法，運用模式識別的理論，結合模糊邏輯和神經網路兩者的優點，進行車型自動分類器設計。 -
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。 -
Based on these algorithms, and consider the property of the arc image, we proposed a new multi - stage algorithm. the proposed algorithm involves the class separability criterion in pattern recognition, and double - threshold method and non - maximum suppression proposed in canny operator. we apply this algorithm to the arc image, and get a better result
並在這些演算法的基礎上，基於電弧圖像的特點，提出了一種改進的多階段邊緣檢測演算法，這個演算法中應用到模式識別中的類別可分離判據的理論，並使用了canny演算法所中提出的雙閾值法和非極大值抑制方法等等。 -
And an intelligent fault detecting system is established. starting from analyzing the possible faults existed ; relations between the fault patterns of the wall - climbing robot and the characteristic signals are established. so the problem of fault detection of the robot is in essence a problem of pattern recognition
主要內容如下：對壁面機器人的可能故障進行分析，總結系統可能的故障類型，並選擇體現不同故障類型的特徵信號，構建系統的故障空間和故障徵兆空間，建立了兩者之間的映射關系，並在此基礎上制定了故障診斷方案。 -
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。
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