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In this paper, we present a method for real-time processing of diffusion tensor and Q-ball imaging.
The need for real-time processing of ''big data" has led to the development of frameworks for distributed stream processing in clusters.
Big Data is a suitable paradigm for real-time processing of large data sets concerning the LS, in the final aim to provide valuable information that may improve the CL experience.
However, because traditional CNN requires the very expensive training time and memory, we design the light CNN consisted of two convolutional layers and two subsampling layers for real-time processing of vehicle applications.
It allows for real-time processing of the collected data.
Clearly, it is unsuitable for real-time processing of streamed image data.
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Synthesis results show that the circuits are suitable for real time processing of various image formats adopted in H.263/MPEG compression standards.
The proposed system is implemented using Hadoop with Spark, voltDB, Storm or S4 for real time processing of the IoT data to generate results to establish the smart city.
Various studies have shown that many-core computing platforms such as OpenCL are among the most promising platforms that are available for real-time processing because of their powerful floating-point computing capabilities.
However, it is difficult for real-time processing because of complicated calculations.
This massive data trove is driving a need for real-time processing and analytics of massive amounts of data.
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