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http://dx.doi.org/10.7742/jksr.2016.10.8.637

Real-time Artificial Neural Network for High-dimensional Medical Image  

Choi, Kwontaeg (Division of Computer Media Engineering, Kangnam University)
Publication Information
Journal of the Korean Society of Radiology / v.10, no.8, 2016 , pp. 637-643 More about this Journal
Abstract
Due to the popularity of artificial intelligent, medical image processing using artificial neural network is increasingly attracting the attention of academic and industry researches. Deep learning with a convolutional neural network has been proved to very effective representation of images. However, the training process requires high performance H/W platform. Thus, the realtime learning of a large number of high dimensional samples within low-power devices is a challenging problem. In this paper, we attempt to establish this possibility by presenting a realtime neural network method on Raspberry pi using online sequential extreme learning machine. Our experiments on high-dimensional dataset show that the proposed method records an almost real-time execution.
Keywords
Medical Imaging; Classification; Artificial Neural Network; ELM; Online Learning;
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