比利斯分類法 的英文怎麼說

中文拼音 [fēnlèi]
比利斯分類法 英文
bliss classification(bc)
  • : Ⅰ動詞1 (比較; 較量高下、 長短、距離、好壞等) compare; compete; contrast; match; emulate 2 (比...
  • : Ⅰ名詞(古代驅疫時用的面具) an ancient maskⅡ形容詞[書面語] (醜陋) ugly
  • : 分Ⅰ名詞1. (成分) component 2. (職責和權利的限度) what is within one's duty or rights Ⅱ同 「份」Ⅲ動詞[書面語] (料想) judge
  • : Ⅰ名1 (許多相似或相同的事物的綜合; 種類) class; category; kind; type 2 (姓氏) a surname Ⅱ動詞...
  • : Ⅰ名詞1 (由國家制定或認可的行為規則的總稱) law 2 (方法; 方式) way; method; mode; means 3 (標...
  1. Finally, a new kind of methods on how to classify a sample into one of the several known populations in terms of posterior probability ratio established by the sample ' s predictive density functions when the unknown parameters " prior distributions are diffuse prior and minnesota prior or normal - inverted wishart distribution

    最後,用參數的充統計量,根據后驗概率構造了一新的基於擴散先驗佈和正態?逆wishart先驗佈的多總體貝葉識別方
  2. This research was conducted to investigate the status quo of cotton production cost in china, based on the data from " the collection for the cost and profit of china agricultural products " published by china plan committee, website of america cotton society and international cotton consultation committee. the present situation of cotton production cost, probable preference of cotton production cost in the key cotton producing provinces in china, the factors that affect the cotton production cost were analyzed from the introduction of the definition, classification and development of cotton production cost by the methods of comparison, probable preference, and multiple regression analysis

    本文以國家計委《全國農產品成本收益資料匯編》 、美國國家棉花協會網站和國際棉花咨詢委員會等發布的棉花生產成本數據為基礎,較、概率優勢、影響因素和回歸等析方,從介紹我國棉花成本的概念、與發展過程入手,析了我國棉花成本的現狀、各產棉省區的成本變動概率優勢、棉花成本的影響因素,並與美國、澳大亞、印度、巴基坦的生產成本進行了橫向較。
  3. Firstly, we directly use the motion vectors of macro - blocks defined in mpeg - i / ii compressing standards and filter the immobile macro - blocks. then, we build a skin color model in ycbcr color space using the convergent property of skin color, and we present the gaussian model skin recognition method and positive - negative look - up table method in details. and we analyze the texture of skin after wavelet transform and present a bayesian method based texture recognition method and a high texture filtering method

    根據皮膚的運動性,首先直接用mpeg -中的壓縮標準中有關宏塊運動預測的方,提取宏塊的運動矢量,將沒有運動的宏塊過濾掉;然後,用皮膚顏色的聚合性,在ycbcr顏色空間建立了皮膚的顏色模型,並別闡述了基於高佈模型的皮膚檢測和正反概率表方;最後,通過對皮膚進行小波變換后的紋理進行統計后,發現有效的用皮膚紋理特徵,可以較有效的過濾掉那些具有似於皮膚顏色的背景,別闡述了基於貝葉的紋理檢測方和高紋理過濾
  4. In the d - s evidence model, we provide two examples, the first case is client evaluation in the bank credit with d - s model, which can be compared with the model of probability. the second case is identification and classification in medical images, which use to explain the applied method

    證據理論推理模型給出了兩個應用實例,一是採用了證據推理模型的銀行信貸客戶評價案例與主觀貝葉進行較,二是用醫學圖像識別示例說明不確定推理的具體應用方
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