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Titlebook: Artificial Intelligence and Signal Processing; International Sympos Ali Movaghar,Mansour Jamzad,Hossein Asadi Conference proceedings 2014 S

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楼主: 叛乱分子
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Contourlet-Based Levelset SAR Image Segmentationots of methods introduced for this purpose in literature. In this paper we used contourlet as a new method for feature extraction. Here the levelset method is used with a statistical based kernel. The parameters of this kernel have been calculated using high order cumulants. For this purpose the est
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Stereo Correspondence Using Hierarchical Belief Propagation and Cross-Based Regionhing algorithm based on Belief Propagation and cross-based aggregation method. In this approach the hierarchical Belief Propagation strategy is followed by a left-right consistency check as an initial match. Then a refinement algorithm is applied to generated disparity map, based on cross-based regi
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Semi-dynamic Facial Expression Recognition Based on Masked Displacement Image methods in recent years. Though dynamic information plays important role in facial expression recognition, utilizing the entire dynamic information of expression image sequences have high computational cost compared to the static cases. In order to reduce the computational cost, only neutral and em
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A Robust and Invariant Keypoint Extraction Algorithm in Brain MR Images brain MR images. In this method, a keypoint is center of a circle which includes circular boundaries in the image and is selected based on gradients of the image. These keypoints and their descriptors are scale and rotation invariant. The proposed method is compared with other well-known methods wi
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Automated Retinal Blood Vessel Segmentation Using Fuzzy Mathematical Morphology and Morphological Ret extracting the retinal images from the background. The changes in the retinal vessels due to the pathologies can be easily identified by segmenting the retinal vessels. In this paper we describe an automatic method for retinal blood vessels segmentation. Segmentation of retinal vessels is done to
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Diagnosing of Fatty and Heterogeneous Liver Diseases from Ultrasound Images Using Fully Automated Seacterize normal, fatty and heterogeneous livers, using textural analysis of liver ultrasound images are described. The proposed algorithm contains two stages. The first stage, automatically assigns some ROIs in a liver ultrasound. In the second stage, discrimination between heterogeneous, fatty and
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