co-occurrence वाक्य
उदाहरण वाक्य
मोबाइल
- Secondly , we review the segmentation methods of image integrated with texture information , and then we make a texture analysis on a human liver ct image through texture feature parameter based on co - occurrence matrix
- Based on the result , a region - growing algorithm is proposed , through extracting texture parameter that based on co - occurrence matrix from image . this method makes use of gray and texture information . finally , the method is implemented by program language
- Based on different texture of the face and the inverse of leather , this paper extracted characteristic vector of the face and the inverse of leather using co - occurrence matrix and classified the face and the inverse of leather using fisher classifier and nn base on characteristic vector
- The " preferring " method , on the other hand , generates semantic restricted rules for each sense - atom according to the co - occurrence sets obtained from a large corpus . this method makes the evaluation of a word by comparing its sense environment and the restricted rules
- The analysis of twenty - two pieces of deceptive confessions shows that five kinds of verbal cues occur with a notable higher frequency than the others in deceptive confessions , the co - occurrence of which well reveals the psychological states and processes of the lying suspects
- A domain - independent dictionary - free lexical acquisition model is presented in this paper , which introduces a self - increasing algorithm to acquire the co - occurrence patterns of chinese characters , and introduces some criteria such as support and confidence to filter these co - occurrence patterns to get lexical items
- Much emphasis has been put on chapter five , which presents a research designed and conducted based on four most influential studies to test the feasibility as well as predictability of some deception detecting criteria from stylistic point of view . after analyzing up to 20 sample hearing transcripts from two highlighted " white - collar " cases , i . e . enron and worldcom , eight stylistic markers derived from previous studies were found to occur in witness / suspect ' s narration , among which five are related to deception at a statistically significant level , with some criteria showing high tendency of co - occurrence
- The author uses the stabilization of parameter to combine the isolated images and process . with the help of matlab plat form , firstly we use binary image , rgb color space and yiq color space , gray co - occurrence matrix and shape analysis to deal with the images , then we use the stabilization of parameter to deal with the data . the result of recognition is good
- In this dissertation a new statistical tool called as grey - primitive co - occurrence matrix is proposed , which is based on predefined specific primitive texture structures . the features extracts from a set of this type matrix can be formed as a primitive texture feature vector and used in retrieving images from image database
- Chapter four describes the method of " preferring " disambiguation . it gives a detailed introduction about the acquirement of the co - occurrence sets , the generation of restricted rules , the determination of the sense environment , and the algorithm of word sense and multiple structure disambiguation
- Among them the gray level co - occurrence matrix ( glcm ) and gray gradient co - occurrence matrix ( ggcm ) methods , which attributed to the statistic textural analysis scheme were then chosen to extract the textural features of five kind areas on satellite images . in the second part the principle of classification and bp neural network were introduced . combined with textural features , the improved bp neural network successfully performed on the classification of the satellite images
- First the sampled image is preprocessed , then five features are extracted from the image preprocessed based on spatial gray level co - occurrence matrix , at last the method of measuring and analyzing of skin texture is proved valid through the result of test of training , classifying and recognizing for skin texture images based on tfbp network
- Based on the experiment datum , the rationality of the selection about cutting parameters is analyzed . the third chapter gives the brief expatiation about the concept of texture . the features of workpiece surface texture are extracted with gray co - occurrence matrix and the disadvantage of this method is pointed out
- In this paper , we made an investigation into texture feature extraction and classification based on statistic method and its application in multi - spectral image classification . the research works of this paper have been done as follows : firstly , in order to overcome the weakness of gray level co - occurrence matrix ( glcm ) , a new unsupervised texture segment algorithm , based on multi - resolution model , is presented in this thesis
- Discovery of association rules is an important class of data mining whose aim is to capture the co - occurrences of itemsets , the most important thing to do is to find the large itemsets effectively , because this is time consuming and will finally decide the efficiency of algorithms . so now the main study is emphasized on how to find the large itemsets with more and more few time
- Discovery of association rules is an important class of data mining whose aim is to capture the co - occurrences of itemsets , the most important thing to do is to find the large itemsets effectively , because this is time - consuming and will finally decide the efficiency of algorithms . so now the main study is emphasized on how to find the large itemsets with more and more few times
- Firstly , for the errors of text �� character and word , utilizing neighborship of character or word , check character and word errors by character string co - occurrence probability . secondly , for the errors of syntax of text , according to statistic and analysis of a large - scale contemporary chinese corpus , recognize the predicate focus word and the others sentence ingredient , check the syntax errors . thirdly , for the errors of text �� semanteme , establishing semantic dependency relationship tree based on hownet knowledge , presents a method that based on semantic dependency relationship analysis to compute sentence similarity , check the semantic errors
- Because this algorithm only include the first order statistical property , but not take the locations of the modulus extrema into account , the second scheme based on the co - occurrence matrix derived form the discrete wavelet frame modulus extrema is proposed , which includes the partial location information extracted from the co - occurrence matrix of the modulus extrema , and so improves the classification performance
- Based on data of sar images which have been pretreated , we apply the gray - level co - occurrence matrix method , and particularly study some texture features used for the classification of sar images , including difference variance difference averages difference entropy contrasts energy s variance sum variances inverse difference moment and correlation etc . furthermore we have abstracted features of sar images
- This dissertation deals with the content - based image retrieval ( cbir ) theory and technique ; some new features and tools for more concisely and discriminatingly charactering the content of an image are proposed , such as region - based color histogram , grey - primitive co - occurrence matrix , ratio of centripetal moment , ratio of eccentric moment and ratio of inertial moment . a new modified genetic algorithm is also described in this dissertation , which can upgrade the performance of standard genetic algorithm ( sga ) while used in image segmentation
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