feature fusion 中文意思是什麼
feature fusion
解釋
特徵融合-
The registration results of computed tomography ( ct ) and magnetic resonance ( mr ) are validated to be subpixel based on mutual information. the fusion of registering ct and mr images by data level fusion or feature level make the information complementarity each other, which realized the anticipative intention
對配準后的ct和mri圖象，通過象素級和特徵級的融合，較好地實現了兩種成像模式的信息互補，達到了預期的實驗要求。 -
Recognition of palm - dorsa vein patterns using multiple feature fusion
多特徵融合的手背血管識別演算法 -
As for feature - level fusion, a new algorithm based on orientation information measurement and his transform is proposed
在特徵級融合方面，提出了一種基於方向性信息測度和ihs變換的圖像融合演算法。 -
Face recognition based on local feature fusion
基於局部特徵融合的人臉識別 -
Face recognition : an approach based on feature fusion and neural network
一種基於特徵融合及神經網路的方法 -
Infrared target recognition method based on invariant fuzzy feature fusion
基於不變性模糊特徵融合的紅外目標識別方法 -
New algorithm for image target recognition based on fractal feature fusion
一種新的基於分形特徵融合的圖像目標識別演算法 -
Based on multi - scale wavelet transform, a multi - feature fusion approach for automatically detecting man - made objects in areas of natural background is proposed
摘要針對自然紋理背景，提出一種基於多尺度小波特徵融合的人造目標檢測方法。 -
The new feature derived from the multiple features fusion benefits from the advantage of single feature to the pattern classifying, which is superior to each fused feature on terms of the classifying performance
由多個特徵融合產生的新特徵吸收了單個特徵的對模式分類的優勢，使它對模式的分類性能優于參與融合的單個特徵。 -
First, a new method of feature level fusion pattern recognition is presented. feature fusion coefficients are defined to fuse the features extracted from different view of multiple sensors. by evaluating different feature fusion coefficients to different features, we can get the fusion feature of the pattern to be observed
首先，提出一種特徵層融合模式識別的方法，定義「特徵融合系數」對多傳感器視角觀察模式所得的不同特徵進行融合，通過對不同特徵賦以不同的特徵融合系數，將多特徵進行融合，得到待識別模式的融合特徵，從而實現特徵層融合。 -
Based on analyzing deeply the basal principle and the system structure of the multi - sensors information fusion technology, and according to the model of feature level fusion, the achieving method of fire detection system based on simulated annealing feature level fusion is presented. this method that searches first - rank ‘ feature fusion coefficient ’ through simulated annealing arithmetic can improve the validity property and demote the mis - warning rate
在深入討論了多傳感器信息融合技術的基本原理及體系結構的基礎上根據特徵層融合的模型提出了基於模擬退火的特徵層融合火災探測系統實現方法，使用模擬退火演算法搜索最佳的「特徵融合系數」 ，從而提高火災探測的正確性，降低誤報率。 -
Experimental results on orl face database show the proposed impca and imlda are more effective and efficient than conventional pca and lda based methods such as eigenfaces and fisherfaces. finally, a strategy of feature parallel fusion is develope
不僅如此，試驗結果還證實了所提出的基丁復線性投影分析的并行特徵融合方法優于傳統的串列特徵融合方法 -
The fusion of stereo vision and laser - radar ( ladar ) is also studied preliminarily in the background of alv navigation. by introducing the ladar data into the height prediction before matching, the fusion can occur on data layer. we have also found and practiced a feature layer fusion method based on dempster - shafer evidential reasoning approach
將激光雷達的測量結果引入立體匹配前的高度預測中，提出了立體視覺與激光雷達在數據層上的信息融合方法;基於d - s證據理論，提出了立體視覺與激光雷達在特徵層上的信息融合方法。 -
Data fusion is a new data processing technique, including three levels of pixel. feature and decision
數據融合是一門新興的數據處理技術，它分為三個層次：象素層、特徵層、決策層。 -
Anova based feature detection for multifocus image fusion
基於方差分析特徵檢測的多聚焦圖像融合方法 -
Fusion algorithms are designed at feature extraction level and matching score level, by concatenating feature vectors, and integrating the matching scores using an adaptive neuro - fuzzy inferencesystem ( anfis ), respectively
最後在特徵提取層和匹配值層設計了融合演算法，分別使用了向量連接法和自適應模糊神經推理系統（ anfis ） 。 -
In the module of vehicle license plate detection, a novel classifier fusion - based algorithm is proposed. after locating candidate license plate regions, features of these regions are extracted for the optimal feature subset by exhaustive search strategy. based on classifier fusion theory, simple average ( sa ) method and two weighted average ( wa ) methods are applied
針對車輛牌照的檢測模塊，提出了一種新的基於分類器融合技術的車輛牌照檢測演算法：從候選車牌區域中提取車牌區域特徵，搜索出候選車牌區域的最佳特徵組合，應用簡單平均運算元和加權平均運算元進行融合判斷，定位車牌區域。 -
For the good stability and validity of the fusion feature, they can be used to ir point target recognition
實驗證明，這一融合特徵矢量具有良好的穩定性和魯棒性，同時該特徵矢量計算量小，有利於工程實現。 -
When it comes to feature - based image fusion, we make use of mean - shift to extract appropriate features according to the characteristics of radarsat and landsat images, then apply the bayes theory to feature level fusion classification
在特徵級的圖像融合中，我們針對radarsat和landsat圖像的特點，採用滑動窗方法提取適當的特徵，然後用bayes理論來進行特徵層的融合分類。 -
The important research is about the theory and methods of the cluster analysis in view of statistical theory, the theory and methods of fuzzy cluster analysis, the fkn " s structure and the fkn ' s study algorithm ( fkn, fuzzy kohonen network ) - the organic fusion of the fuzzy c - means algorithm and self - organized feature map neural network. the paper proposes the ifkn ( improved fkn ) on the basis of the hard classification idea and the soft classification idea, then carries on the cluster analysis of the artificial synthetic control chart time series through matlab program and tt ? cluster result matches the cluster result of the famous dataengine " s software of the intellectual data analysis and data mining from german mit company. finally, the paper discusses the applying of the cluster analysis to the control process, which can be widely applied to the pattern recognition of the parameter " s changing trend during the control process and the image partition processing, and utilizes the ifkn to recognize the thermotechnical parameter " s changing trend based on the engineering of clinker sintering rotary kiln automatic control system of guizhou " s aluminium factory, through which good effect is obtained
數據挖掘技術在商業領域中已廣泛使用，然而在工業過程式控制制中的應用卻極少，本文正是在這種背景下，對數據挖掘中的聚類分析方法及其在工業過程式控制制中的應用研究作了償試，重點研究了基於統計理論的聚類分析理論和方法，模糊聚類分析理論和方法及模糊kohonen網路（ fkn ）的結構與學習演算法，即模糊c ? ?均值演算法與自組織特徵映射神經網路（ kohonen網路）的有機融合，並根據硬分類思想及軟分類思想提出了改進的模糊kohonen網路（ ifkn ） ，通過matlab編程對人工合成控制時序圖數據集進行聚類分析，其聚類效果與當今廣泛使用的數掘挖掘軟體平臺，德國mit公司著名的dataengine智能數據分析和數掘挖掘軟體的聚類效果相當，最後，論述了聚類分析在控制中的應用，它可以用於過程式控制制中的參數變化趨勢的模式識別及圖象分割處理等具體應用中，並以貴州鋁廠熟料燒結回轉窯自動控制系統為工程背景，利用ifkn識別其熱工參量變化趨勢，取得了較理想的效果。
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