nearest neighbor search造句
例句與造句
- 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 - It's difficult to find nearest neighbor search in a sentence. 用nearest neighbor search造句挺難的
- 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(lái)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(wú)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(guò)程較慢的問(wèn)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(lái)完成傳統(tǒng)算法中最耗時(shí)的最近鄰搜索過(guò)程，減少了完成訓(xùn)練所需乘法次數(shù)。