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pattern classification是什麼意思,pattern classification的意思翻譯、用法、同義詞、例句

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  • [計] 模式分類

  • 例句

  • Machine fault diagnosis is a problem of pattern classification in nature.

    機械故障診斷本質上是一個模式分類問題。

  • The linear discriminant function is a basic method of the computer pattern classification.

    線性判别函數法是計算機模式分類的一種基本方法。

  • In this paper we look into the application of moment function and neural network in feature extraction and pattern classification of image recognition respectively.

    本文主要研究了矩函數和神經網絡分别在圖像識别的特征提取和模式分類方面的應用。

  • As a method of neural network, the self-organizing map(SOM) is an excellent tool for data mining, machine learning and pattern classification.

    自組織特征映射作為一種神經網絡方法,在數據挖掘、機器學習和模式分類中得到了廣泛的應用。

  • It has payed great attention to effective training of feedforward neural networks when they are used for pattern classification.

    前向網絡在用于模式分類時,其網絡的有效訓練一直是一個受到關注的問題。

  • The neural network using in pattern classification problems mostly adopt multi-layer feed-forward neural network and use the back-propagation algorithm (BP algorithm).

    用于模式分類問題的神經網絡大多數采用多層前向神經網絡,并且使用反向傳播算法(BP算法)。

  • Several typical examples of pattern classification are stu***d with computer simulation.

    對模式分類的幾個典型例子進行了計算機仿真研究。

  • Face recognition normally be regarded as have three processes that are face detection, features extraction and pattern classification.

    人臉識别一般分為人臉檢測、特征抽取和模式分類三個部分。

  • A pre-grasp pattern classification method based on the computer vision and the improved fuzzy C-means clustering algorithm is introduced.

    提出一種基于計算機視覺的,以及改進的模糊C均值聚類算法的機器人多指手預抓取模式分類方法。

  • This paper proposes an algorithm of image segmentation based on pattern classification according to the features of soil microphotographs.

    該文針對土壤顯微圖片特征,基幹模式分類對圖象實施分割;

  • This paper is a summary about the feature extraction and selection, the traditional methods, together with its researching situation, of the pattern classification and recognition.

    綜述了模式分類與識别中的特征抽取與選擇、模式分類與識别的傳統方法及其研究狀況,同時也簡介了模式識别中并行處理方法的進展。

  • Its effectiveness has been testified by computer simulating experiment and it can be regarded as a promising machine learning for the pattern classification system.

    該算法的有效性已由計算機仿真實驗所證實,可被認為是一種很有發展前途的模式分類系統的機器學習算法。

  • The simulations of several typical problems such as n-pity, function approximation and pattern classification problem are made to verify the validity of the proposed method.

    并通過對奇偶問題、非線性函數逼近問題、模式分類問題等的仿真,驗證了所提出方法的有效性。

  • In this paper, we propose to use ART1 Network a neural network to do pattern classification and anomaly detection for linux process behavior, primary experiments suggest that this method is feasible.

    本文利用ART1網絡對進程的系統調用序列進行模式提取, 據此進行異常檢測, 并以實驗數據初步驗證了該方法的可行性。

  • This algorithm improves the recognition rate of pattern classification algorithms.

    本算法提高了模式分類算法的辨識率。

  • However, these responses are still possibly useful for such applications as associative memory and pattern classification because of robustness in output precision.

    然而,由于輸出精度的魯棒性,這些響應仍可能對結合存儲器和模式分類的應用有效。

  • The eight-dimension features have different effect in pattern classification process due to different characters.

    由于每項特征的特異性不同,在模式分類中起到的作用也不同。

  • Similar asface recognition, gender classification consists of three main parts: image preprocessing, feature extraction and pattern classification.

    與人臉識别類似,性别分類主要分為圖像預處理,特征提取和模式分類等三個部分。

  • The self-organizing feature maps (SOFM) neural network, which is widely used in pattern classification of data set, is applied to hydrological regionalization of Jiangsi and Fujian Provinces, China.

    水文分區問題是模式分類問題的一種,本文采用已被廣泛應用于模式分類問題中的自組織特征映射人工神經網絡(SOFM網絡)方法對江西和福建兩省進行水文分區。

  • This thesis discussed mainly about its application on spectra library search and pattern classification, etc.

    本論丈主要讨診它在講庫檢索和模式分類中的應用。

  • It is well known that, counter propagation network is fitful for pattern classification. According to such attribute, we present a face recognition algorithm based on counter propagation network.

    根據對向傳播網絡適于模式分類的特性,提出了基于對向傳播網絡的人臉識别方法。

  • Pattern classification was an important part of the RBF neural network application.

    模式分類是RBF神經網絡應用的一個重要方面。

  • The theory of SVM is stu***d at first, then an ameliorated RBF kernel function is presented, based on which an improved kernel function pattern classification method of SVM is put forward.

    首先分析了支持向量機原理,隨後引入一種改進的徑向基核函數,在此基礎上,提出了一種改進核函數的SVM模式分類方法。

  • Some key issues of pattern classification for Boolean vector data are put forward and stu***d in the dissertation, and research results are applied into TCM diagnosis scale development.

    論文提出和研究了布爾向量數據模式分類中的關鍵問題,并将研究結果應用于中醫學診斷量表研制當中。

  • Pattern classification is a kind of technology used in a lot of project fields including automatic control monitor, image recognition, troubled diagnose, supplies compound, medical diagnosis, etc.

    模式分類是許多工程領域如自控監測、圖像識别、故障診斷、物料配制、醫療診斷等領域廣泛應用的一種關鍵技術。

  • An evolving neural network classifier using variable string genetic algorithm(VGA) was developed to study pattern classification for image and speech.

    為研究圖像和語音的模式分類,提出一種采用可變長度串遺傳算法(VGA)的進化神經網絡。

  • Then damage identification of severity of bolt looseness was stu***d by utilizing the pattern classification function of the BP neural network.

    然後利用BP神經網絡的模式分類功能,進行了螺栓松動程度的損傷識别研究。

  • The outlier identification is divided into two sequential parts: the robust day-load-curves cluster and the bad curve pattern classification.

    負荷壞數據辨識是由負荷曲線聚類和壞數據曲線模式分類兩個順序的過程組成的;

  • 專業解析

    模式識别與分類的詳細解釋

    1. 模式(Pattern)

    在科學和工程領域,"pattern"指可重複觀測的數據結構或規律。例如,在機器學習中,模式可以是圖像中的邊緣特征、語音信號中的頻譜特征,或是時間序列數據中的周期性變化。模式識别(Pattern Recognition)是通過算法從原始數據中提取并分析這些規律的過程,常用于圖像處理、自然語言處理等領域。

    2. 分類(Classification)

    "Classification"是模式識别的核心任務之一,指根據已知特征将數據劃分到預定義類别中的過程。例如,垃圾郵件過濾器通過分析郵件文本特征(如關鍵詞、發件人),将其分類為“垃圾”或“正常”。常見的分類算法包括支持向量機(SVM)、決策樹和神經網絡。

    3. 模式與分類的結合應用

    兩者的結合體現在“模式分類”(Pattern Classification)中,即通過提取數據模式并匹配到特定類别實現自動化決策。例如:

    權威參考來源

    網絡擴展資料

    “Pattern classification”(模式分類)是機器學習和模式識别領域的核心概念,指根據數據的特征将其劃分到預定義類别的過程。以下是詳細解釋:

    1.定義

    模式分類是通過分析輸入數據的特征(如形狀、顔色、統計屬性等),利用數學模型或算法将其歸類到已知類别中的技術。例如,識别手寫數字屬于0-9中的哪一個,或判斷醫學影像是否顯示病變。

    2.關鍵步驟

    3.應用領域

    4.分類方法

    5.挑戰與限制

    模式分類是人工智能的基礎技術,其發展推動了自動駕駛、智能助手等應用的進步。實際應用中需結合領域知識優化特征選擇和模型設計,以達到最佳效果。

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