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There arises the needs for fast processing of continuous video data using embedded devices, for example the one needed for UAV aerial photography. In this paper, we proposed a distributed embedded platform built with NVIDIA Jetson TX1 using deep learning techniques for real time video processing, mainly for object detection. We design a Storm based distributed real-time computation platform and ran...
Video data has become the largest source of big data. Owing to video data's complexities, velocity, and volume, public security and other surveillance applications require efficient, intelligent runtime video processing. To address these challenges, a proposed framework combines two cloud-computing technologies: Storm stream processing and Hadoop batch processing. It uses deep learning to realize...
With the rise of video surveillance applications for analyzing real-time and batching video data in large scales, traditional video processing systems are being challenged due to real-time, intelligence and fault-tolerance demand for networked high resolution and large-scale video processing. These challenges can be further exacerbated by the existing predicaments of multi-platform, multi-format,...
As the rapid development of China's highway construction, the rationality of the design of public transport routes has to face a severe test, since a static bus system can not keep up with the social life nowadays. In this article, we will talk about using the ArcGIS Server technology to develop a dynamic bus monitoring and scheduling system, which combines 3S technology (GPS, RS, GIS) together, to...
SAT-based bounded model checking has a high complexity in dealing with real-time systems. SMT solvers can generalize SAT solving by adding the ability to handle arithmetic and other decidable theories. With this advantage, if we use SMT in bounded model checking for real-time systems instead of SAT, the clocks can be represented as integer or real variables directly and clock constraints can be represented...
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