nearest neighbor search 中文意思是什麼

nearest neighbor search 解釋
最近點對查詢
  • nearest : ad. 最近的,最親近的
  • neighbor : n 1 鄰人 鄰居;鄰近的人;鄰國(人)。2 鄰座(的人);鄰接的東西。3 同胞;世人。4 (對任何不知姓名...
  • search : vt 1 搜查;檢查(身體、衣袋等);搜索,搜尋;找;尋找。2 調查;查究;探求;追求;根究 (into)。3...
  1. 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.

    在估計網路結點值時,部分起用以另一個因素及對最鄰近點搜尋中找出的不同數據值所給的權。
  2. 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上提出了等和值塊擴展最近鄰快速碼字搜索演算法( ebnns ) ,該演算法在圖像畫質達到窮盡搜索演算法的前提下,大大降低了碼字搜索率和硬體實現面積;為了提高編碼效率,在相關性編碼方面,提出了相關繼承編碼演算法,對普通矢量量化后的編碼索引進行無損重編碼。
  3. Nearest neighbor search

    最近點對查詢
  4. Constrained nearest neighbor search on moving objects trajectories

    即約束的移動對象最近鄰軌跡
  5. Nearest neighbor search for constrained moving objects trajectories

    約束的移動對象最近鄰軌跡查詢
  6. An optimal projection and dynamic threshold based nearest neighbor search algorithm

    基於遺傳演算法的模糊多閾值圖像分割方法
  7. Efficient k - nearest - neighbor search algorithms for historical moving object trajectories

    有效的歷史移動對象軌跡的k最近鄰居查找演算法
  8. K nearest neighbor search is one of the most important operations in spatial and spatio - temporal databases

    在諸如此類的應用中,一個重要的查詢類型就是k最近鄰居knn查找。
  9. The new improved nearest neighbor search algorithm presented based on key dimension, which could be used to improve the performance of compute efficiency

    為降低計算時間,提出一種基於關鍵維的近鄰搜索演算法。
  10. On the other side, we use nearest neighbor approximation to calculate gussian mixture densities, which can reduce recognition time by 6. 67 % compared with standard viterbi beam search algorithm

    另一方面,使用高斯混合概率密度的最近鄰快速估算方法,使標準viterbibeam搜索演算法的搜索速度提高了6 . 67 。
  11. Further more, we improve the nearest neighbor approximation method by calculat e mixtures ordered by likelihood of being the best scoring mixture. the likelihood is calculating from previously processed data. this improved method can reduce recognition time by 15. 56 % compared with standard viterbi beam search algorithm

    本文對最近鄰快速估算方法進行改進,在搜索過程中根據已處理過的數據統計出各個高斯混合分量產生最高對數概率的概率,並依此預測隨后的計算中最有可能產生最高對數概率的高斯混合分量,優先計算更有可能產生最高對數概率的高斯混合分量,使標準viterbibeam搜索演算法的搜索速度提高了15 . 56 。
  12. The parallel search computing method based on the case has many kinds, the parallel fuzzy inference method is introduced in the paper. the nearest neighbor approach is studied in the third chapter. and as to similarity assessment of numerical features is difficult, an assessment method of similarity between numerical features is built on the basis of fuzzy dissertation

    在案例間相似度的計算方法中,本文介紹了最鄰近匹配函數演算法,針對最鄰近匹配中定量特徵的相似度評估難的問題,建立了一種基於模糊劃分的定量特徵相似度評估方式。
  13. In this paper, a novel - it composite distance transformation method, which is called cdt, is proposed to support a fast k - nearest - neighbor k - nn search in high - dimensional spaces

    提出一種新型的基於復合距離轉化的索引方法cdt composite distance transformation ,以支持快速的k近鄰查詢。
  14. 1998, 27 : 16 - 21. 7 frentzos e, gratsias k, pelekis n, theodoridis y. nearest neighbor search on moving object trajectories. in proc

    他們在由tb樹索引的數據集上利用一個深度優先df搜索範例來處理移動對象軌跡的knn查找。
  15. 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

    摘要針對傳統的自組織映射網路在大數據量或高維情形下訓練過程較慢的問題,提出了分別使用部分失真搜索和擴展的部分失真搜索來完成傳統演算法中最耗時的最近鄰搜索過程,減少了完成訓練所需乘法次數。
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