Titlebook: Big Data and Visual Analytics; Sang C. Suh,Thomas Anthony Conference proceedings 2017 Springer International Publishing AG 2017 Big data.B

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與野獸博斗者

Swarm Intelligence Applied to Big Data Analytics for Rescue Operations with RASEN Sensor Networks,d technology, cyber-physical system platforms, and algorithms exist which can coordinate rescue operations utilizing swarm intelligence with Rapid Alert Sensor for Enhanced Night Vision (RASEN). We will also introduce biologically inspired algorithms combined with proposed fusion night vision techno

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Blatant

Scalable Gene Sequence Analysis on Spark,equences, and analysis of such large-scale sequencing data is the primary concern. This chapter introduces a scalable genome sequence analysis system, which makes use of parallel computing features of Apache Spark and its relational processing module called Spark Structured Query Language (Spark SQL

結(jié)構(gòu)

Big Sensor Data Acquisition and Archiving with Compression,tion of sensor data and the storage of massive sensor data collection. These data sources generate so much data quickly that data compression is essential to reduce storage requirement or transmission capacity of devices. This work first discusses a low complexity sensing framework which enables to

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Mammal

A Big Data Analytics Approach in Medical Imaging Segmentation Using Deep Convolutional Neural Netwoloping solutions from large datasets, and is an important tool in the big data analytics toolbox. Deep Learning has been recently employed to solve various problems in computer vision and demonstrated state-of-the-art performance on visual recognition tasks. In medical imaging, especially in brain t

迫擊炮

Big Data in Libraries,he three Vs): Volume, Velocity and Variety. Laney [1, 2] Each of these has different challenges. Huge volumes of data require the ability to store and retrieve the data efficiently. High velocity data requires the ability to ingest the data as it is created, essentially very fast internet connection