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nearest neighbor search中文是什么意思

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  • 例句與用法
  • An additional factor which plays apart in estimation of the values at the grid nodes is weighting to be placed on the different data values located by the nearest neighbor search .
    在估計(jì)網(wǎng)絡(luò)結(jié)點(diǎn)值時(shí),部分起用以另一個(gè)因素及對(duì)最鄰近點(diǎn)搜尋中找出的不同數(shù)據(jù)值所給的權(quán)。
  • Constrained nearest neighbor search on moving objects trajectories
    即約束的移動(dòng)對(duì)象最近鄰軌跡
  • Nearest neighbor search for constrained moving objects trajectories
    約束的移動(dòng)對(duì)象最近鄰軌跡查詢
  • An optimal projection and dynamic threshold based nearest neighbor search algorithm
    基于遺傳算法的模糊多閾值圖像分割方法
  • Nearest neighbor search
    最近點(diǎn)對(duì)查詢
  • K nearest neighbor search is one of the most important operations in spatial and spatio - temporal databases
    在諸如此類的應(yīng)用中,一個(gè)重要的查詢類型就是k最近鄰居knn查找。
  • The new improved nearest neighbor search algorithm presented based on key dimension , which could be used to improve the performance of compute efficiency
    為降低計(jì)算時(shí)間,提出一種基于關(guān)鍵維的近鄰搜索算法。
  • 1998 , 27 : 16 - 21 . 7 frentzos e , gratsias k , pelekis n , theodoridis y . nearest neighbor search on moving object trajectories . in proc
    他們?cè)谟蓆b樹索引的數(shù)據(jù)集上利用一個(gè)深度優(yōu)先df搜索范例來處理移動(dòng)對(duì)象軌跡的knn查找。
  • Firstly , based on conventional vq , a fast algorithm named equal - sum block - extending nearest neighbor search ( ebnns ) is presented , which not only can achieve the reconstructed image of full search algorithm but also can greatly reduce both the codeword search ratio and chip area . in order to improve coding efficiency , a new algorithm called correlation - inheritance coding is proposed , which is embedded in conventional vq system to improve compression ratio by re - encoding the indexes
    首先,在普通矢量量化基礎(chǔ)上提出了等和值塊擴(kuò)展最近鄰快速碼字搜索算法( ebnns ) ,該算法在圖像畫質(zhì)達(dá)到窮盡搜索算法的前提下,大大降低了碼字搜索率和硬件實(shí)現(xiàn)面積;為了提高編碼效率,在相關(guān)性編碼方面,提出了相關(guān)繼承編碼算法,對(duì)普通矢量量化后的編碼索引進(jìn)行無損重編碼。
  • To accelerate the learning process of self - organizing mapping in the situation of large mount of data or high dimension , two learning algorithms were proposed in this paper , by using partial distortion search and extended partial distortion search respectively to solve the problem of nearest neighbor search during learning process , which could reduce the multiplications greatly
    摘要針對(duì)傳統(tǒng)的自組織映射網(wǎng)絡(luò)在大數(shù)據(jù)量或高維情形下訓(xùn)練過程較慢的問題,提出了分別使用部分失真搜索和擴(kuò)展的部分失真搜索來完成傳統(tǒng)算法中最耗時(shí)的最近鄰搜索過程,減少了完成訓(xùn)練所需乘法次數(shù)。
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