this paper describes some applications of the recently introduced Intelligent Localized Fusion (ILF) paradigm in multisensorial computer vision systems. the paradigm is based on a new interpretation of the fuzzy integ...
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In this study we propose a strategy for the follow-up of the process behavior and detection of failures. An approach of industrial diagnosis based on the statistical patternrecognition Neuro-Fuzzy being based on a di...
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ISBN:
(纸本)9788890372476
In this study we propose a strategy for the follow-up of the process behavior and detection of failures. An approach of industrial diagnosis based on the statistical patternrecognition Neuro-Fuzzy being based on a digital representation and symbolic system of the forms is implemented. Within this framework, data-processing interactive software of simulation baptized NEFDIAG (NEuro Fuzzy DIAGnosis) version 1.0 is developed. this software devoted primarily to creation, training and test of a classification Neuro-Fuzzy system of industrial process failures. NEFDIAG can be represented like a special type of fuzzy perceptron, withthree layers used to classify patterns and failures. the system selected is the workshop of SCIMAT clinker, cement factory in Algeria.
Liver biopsy is considered as mandatory for the management of patients infected withthe hepatitis C virus (HCV), particularly for staging of fibrosis degree. However, due to its invasive nature and limitations of sam...
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ISBN:
(纸本)9781424471706
Liver biopsy is considered as mandatory for the management of patients infected withthe hepatitis C virus (HCV), particularly for staging of fibrosis degree. However, due to its invasive nature and limitations of sampling error, the tendency is to substitute the liver biopsy with non-invasive method. the objective of this study is to combine the serum biomarkers and histopathological findings to develop a classification model that can predict the hepatic fibrosis stage. the best developed classification model was able to predict the different fibrosis grades with accuracy of 93.7%. this accuracy represents a substantial improvement over previous works and would pave the way to utilize classification models as a clinically non-invasive and reliable method to assess the degree of liver fibrosis.
We investigate the effect of quantified statistical facial asymmetry as a biometric under expression variations. Our findings show that the facial asymmetry measures (AsymFaces) are computation ally feasible, containi...
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ISBN:
(纸本)0769516025
We investigate the effect of quantified statistical facial asymmetry as a biometric under expression variations. Our findings show that the facial asymmetry measures (AsymFaces) are computation ally feasible, containing discriminative information and providing synergy when combined with Fisherface and Eigen-face methods on image data of two publically available face databases (Cohn-Kanade and Feret).
In this paper, we present a local morphological pattern spectrum based approach for off-line signature verification. the proposed approach has three major phases : Preprocessing, Feature extraction and Classification....
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Manifold learning has currently become a hot issue in the field of machine learning, patternrecognition and data mining. Locally linear embedding (LLE) is one of several promising manifold learning methods. But ordin...
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ISBN:
(纸本)9780769533056
Manifold learning has currently become a hot issue in the field of machine learning, patternrecognition and data mining. Locally linear embedding (LLE) is one of several promising manifold learning methods. But ordinary LLE can not distinguish effectively the low-dimensional embeddings of noise data. By introducing the reconstruction similarity into LLE, this paper proposes a generalized locally linear embedding algorithm based on local reconstruction similarity. Experimental results show on Columbia object image data that the new generalized version is superior to LLE in revealing the visualization of high-dimensional image dataset containing noise images.
Iris segmentation has been an especially interesting research area from the last decade due to the increased security conditions for the sophisticated personal identification ideas based on biometrics. the rich distin...
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ISBN:
(纸本)9781538695333
Iris segmentation has been an especially interesting research area from the last decade due to the increased security conditions for the sophisticated personal identification ideas based on biometrics. the rich distinctive and stable textural information of the iris models make iris a biometric modality for identifying each person correctly and reliably. Most recent iris segmentation techniques show the high segmentation accuracies in cooperative environments. However, the iris image segmentation remains a difficult topic. In this frame work, we proposed an innovative model as an improvement of Chan-Vese technique by incorporating B spline approach to perform iris segmentation. Proposed scheme has added enhanced segmentation for non-ideal iris images in visible light. the GLCM (Gray Level Co-occurrence Matrix) and LBP (Local Binary pattern) are employed for feature extraction. this scheme is able to perform all the associated treating in 1-dimension as the B-spline task is divisible and is built as the result of n-1), 1-D, B-splines. this presents superior control compared to other methods. Experimental results displays that the proposed iris segmentation technique considerably minimizes the required time to segment the iris without affecting the segmentation precision. the main benefits of this algorithm are: First, it can deal withthe accurate recognition of smooth objects. Second one is, it can powerfully handle the noisy images. therefore, thereal boundaries are conserved and correctly distinguished Additionally the comparison outcomes with related iris segmentation methods show the superiority of the proposed work in terms of segmentation accuracy and recognition performance. the NICE I iris image database is used to compute the performance of the proposed technique.
the power grid lines and equipment maintenance of power enterprises is a complicated construction process, the cost of which is affected by meteorological and geographical factors, and the influence mode is uncertain....
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the power grid lines and equipment maintenance of power enterprises is a complicated construction process, the cost of which is affected by meteorological and geographical factors, and the influence mode is uncertain. Using fuzzy clustering method and the threshold intervals of the objective function in clusters, this paper builds a predictive control model to control the project cost. this model uses relative fuzzy operator to build fuzzy matrix, construct correlation between factors, and describe the factors' effect. Extracting the cluster's eigenfunction, and defining the boundaries of various clusters, we determined the type of the predicted points and the range of the objective function. When the actual cost of the maintenance project is within the range calculated by the cost model, then it is normal. If the actual cost exceeds this range, then further analysis of all the aspects of the cost is needed to find out the reason.
Concavity trees are structures for 2-D shape representation. In this paper, we present a new recursive method for concavity tree matching that returns the distance between two attributed concavity trees. the matching ...
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ISBN:
(纸本)3540225706
Concavity trees are structures for 2-D shape representation. In this paper, we present a new recursive method for concavity tree matching that returns the distance between two attributed concavity trees. the matching is based both on the structure of the tree as well as on the attributes stored at each node. Moreover, the method can be implemented on parallel architectures, and it supports occluded and partial matching. To the best of our knowledge, this is the first work to detail a method for concavity tree matching. We test our method on 625 silhouettes in the context of shape-based nearest-neighbour retrieval.
Parser plays a very important role in computational linguistics. In this paper, here we describe a parsing technique for Bangla grammar recognition. the parser is, by nature, a shift reduce parser and constructs a par...
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ISBN:
(纸本)9781509012695
Parser plays a very important role in computational linguistics. In this paper, here we describe a parsing technique for Bangla grammar recognition. the parser is, by nature, a shift reduce parser and constructs a parse table based on LR strategy. It takes the Context Free Grammar (CFG) of the Bangla language as input and constructs parser table from the grammar. the parse table is visited on bottom-up approach. this parser is free from the problem of the left factoring and left recursion. To avoid the inflection (BIVOKTI) of Bangla we describe a new approach. Hence only the main form of the Bangla word is stored in the repository. Our experiment shows that the scheme can detect all forms of Bangla sentences even for nontraditional forms.
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