Titlebook: Cognitive Systems and Signal Processing; 4th International Co Fuchun Sun,Huaping Liu,Dewen Hu Conference proceedings 2019 Springer Nature S

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https://doi.org/10.1007/978-3-322-86768-1ormance, we use convolution neural network (CNN) based deep learning method to classify ihomogeneous rock images intelligently. We present the depthwise separable convolution method for rock image classification, which reduces the required parameters compared to normal convolution, and achieves the

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Communications in Computer and Information Sciencehttp://image.papertrans.cn/c/image/229138.jpg

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Programme mit globalem Speicher,ipid plaque areas in real-time with better time-efficiency and competitive accuracy during the diagnosis. SSPM is tested on IV-OCT human coronary artery imaging dataset, and the result shows that our method is able to mark suspicious lipid-plaque areas at 91 fps on GPU, or 16 fps on CPU, with an accuracy of 87%.