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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...
Big data analytics (BDA) applications are software applications that process huge amounts of data using large-scale parallel processing infrastructure to obtain hidden value. Hadoop is the most mature open source BDA processing framework, which implements the MapReduce programming paradigm. In many cases, BDA jobs are continuous and not mutually separated. Existing work on processing jobs in sequence...
Big Data processing has become the common business needs in government and enterprise applications, e.g., Analysis or detection of climate change, economic development, or online customer behavior. Hadoop is the most mature open source big data processing framework, which implements the MapReduce programming paradigm. The mass source data are stored in HDFS supported by Hadoop and processed parallelly...
Due to complexities of big video data management, such as massive processing of large amount of video data to do a video summary, it is challenging to effectively and efficiently store and process these video data in a user friendly way. Based on the parallel processing and flexible storage capabilities of cloud computing, in this paper, we propose a practical massive video management platform using...
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