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In recent years, increasing attention has been paid to developing exceptional technologies for efficiently processing massive collection of data. This is essential in the research on smart city, which involves various types of data generated by different kinds of sensors (hard and soft). In this paper, we propose a cloud-based platform named City Digital Pulse (CDP), where a unified mechanism and...
Image processing is an important phase in order to improve the accuracy both for diagnosis procedure and for surgical operation. Medical diagnosis is one of the most important areas in which image processing procedures are usefully applied. In this paper, we use the Cellular Neural Networks to research diagnostic images. We present a robustness design theorem for the optimal edge detector cellular...
In this paper, we combine cellular neural network (CNN) and gray step co-occurrence matrix to process B-scan images of fatty patients' livers. We deal with the B-scan images of fatty patients' livers by the edge detection cellular neural network, and then analyze the B-scan image features, including the co-occurrence matrix's contrast (Contrast), correlation (Correlation), energy (Energy) and homogeneity...
In this paper, first, the counter detection (CD) cell nerve net (CNN) has been applied to preprocessing ultrasound B-scan images of patients' livers. Second, the preprocessed images are further converted via Fourier transform. The maximal elements of the transformed matrix of the ultrasound B-scan images seem to be relation with the degrees of the damages of patient's livers. If using Fourier transform...
This paper presents a theorem for designing the robustness template parameters of a cellular neural network (CNN) to detect contours in images. The theorem provides parameter inequalities for determining parameter intervals to implement corresponding tasks. As two first examples, the contour detection (CD) CNN has successfully detected contours in a grey pattern image and the Lena portrait. As the...
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