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Description
  • After a brief introduction to principles of Cortical Learning Algorithm (CLA) and Hierarchical Temporal Memory (HTM) which frame the theory for NuPIC – a human neocortex-inspired neural network implementation, we focus on practical use-cases in context of Smart Homes: 1) processing bio-signals (ECG classification, prediction, anomaly detection) for the purpose of mobile assisted technologies. 2) prediction of sensory and location data in smart homes. Preliminary results, realized and in-progress projects are presented in this study as well as obstacles and some comparison to other solution for these ML tasks.
  • After a brief introduction to principles of Cortical Learning Algorithm (CLA) and Hierarchical Temporal Memory (HTM) which frame the theory for NuPIC – a human neocortex-inspired neural network implementation, we focus on practical use-cases in context of Smart Homes: 1) processing bio-signals (ECG classification, prediction, anomaly detection) for the purpose of mobile assisted technologies. 2) prediction of sensory and location data in smart homes. Preliminary results, realized and in-progress projects are presented in this study as well as obstacles and some comparison to other solution for these ML tasks. (en)
Title
  • Anomaly Detection with Cortical Learning Algorithm for Smart Homes
  • Anomaly Detection with Cortical Learning Algorithm for Smart Homes (en)
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  • Anomaly Detection with Cortical Learning Algorithm for Smart Homes
  • Anomaly Detection with Cortical Learning Algorithm for Smart Homes (en)
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  • RIV/68407700:21230/14:00224795!RIV15-MSM-21230___
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  • 3335
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  • RIV/68407700:21230/14:00224795
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  • Anomaly Detection in ECG/Position; Cortical Learning; Bio-Sensors; Monitoring; HTM/CLA, NuPIC (en)
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  • [9B3D974DD0D3]
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  • Praha
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  • Praha
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  • Proceedings of 3rd Conference on Innovations in Assistive Technologies and Health Care
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  • Štěpánková, Olga
  • Otáhal, Marek
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number of pages
http://bibframe.org/vocab/doi
  • 10.13140/2.1.2927.8405
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  • České vysoké učení technické v Praze. Fakulta elektrotechnická
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  • 978-80-01-05572-4
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  • 21230
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