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A novel method, called grayscale iteration threshold pulse coupled neural network (GIT-PCNN) was proposed for image segmentation, which integrates grayscale iteration threshold with PCNN. PCNN has been widely used in image segmentation. However, satisfactory results are usually obtained at the expense of time-consuming selection of PCNN parameters and the number of iteration. In this method, traditional...
Minimum redundancy maximum relevancy (mRMR) is one of the successful criteria used by many feature selection techniques to evaluate the discriminating abilities of the features. We combined dynamic sample space with mRMR and proposed a new feature selection method. In each iteration, the weighted mRMR values are calculated on dynamic sample space consisting of the current unlabelled samples. The feature...
To reduce noise and speckles in the spectrograms of Doppler blood flow signals, a novel method, called matching pursuit with pulse coupled neural network (MPPCNN), has been proposed. The method considered is an iterative decomposition algorithm, which decomposes the Doppler ultrasound signals into linear expansion of atoms in a time-frequency dictionary using the matching pursuit (MP) for de-noising...
This study describes a new method for segmentation of Synthetic Aperture Radar (SAR) images, which integrates optimal threshold with pulse-coupled neural network (PCNN). Traditional image segmentation algorithms exhibit weak performance for SAR images due to the poor quality of SAR images. PCNN has been widely used in image segmentation. However, satisfactory results are usually obtained at the expense...
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