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Mass detection in mammograms is a challenging problem. In this paper, we propose a cost-sensitive cascaded method for automatic mass detection, which employs machine learning techniques to detect region of interests (ROI). In detail, we divide the original mammograms into overlapped squared sub-images. For each sub-image, intensity features based on gray histogram, texture features based on spatial...
A valid recognition technology of sintering state based on advanced genetic algorithm (GA) and artificial neural network (ANN) is presented Then important features are extracted and are selected from sintering images by some image processing methods, and GA is used to optimize the parameters of modified ANN. Lastly recognize the sintering state with ANN method. The results show that the strategy can...
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