Autonomous penetration detection for bone cutting tool using demonstration-based learning
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: 2014شناسه الکترونیک: 10.1109/EMBC.2014.6944578
کلیدواژه(گان): Big Data,biomedical equipment,data analysis,decision support systems,feature extraction,feature selection,health care,knowledge acquisition,medical computing,patient care,patient monitoring,surgery,ICU datasets,analytical tools,big data handling,biomedical instrumentation,clinical decisions,data categorization,data preprocessing,data-driven analytics,data-driven knowledge extraction,data-driven methodology,data-driven methods,data-rich environment,database,feature extrac
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Autonomous penetration detection for bone cutting tool using demonstration-based learning
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date accessioned | 2020-03-12T20:47:23Z | |
date available | 2020-03-12T20:47:23Z | |
date issued | 2014 | |
identifier other | 6906624.pdf | |
identifier uri | https://libsearch.um.ac.ir:443/fum/handle/fum/1025547 | |
format | general | |
language | English | |
publisher | IEEE | |
title | Autonomous penetration detection for bone cutting tool using demonstration-based learning | |
type | Conference Paper | |
contenttype | Metadata Only | |
identifier padid | 8150550 | |
subject keywords | Big Data | |
subject keywords | biomedical equipment | |
subject keywords | data analysis | |
subject keywords | decision support systems | |
subject keywords | feature extraction | |
subject keywords | feature selection | |
subject keywords | health care | |
subject keywords | knowledge acquisition | |
subject keywords | medical computing | |
subject keywords | patient care | |
subject keywords | patient monitoring | |
subject keywords | surgery | |
subject keywords | ICU datasets | |
subject keywords | analytical tools | |
subject keywords | big data handling | |
subject keywords | biomedical instrumentation | |
subject keywords | clinical decisions | |
subject keywords | data categorization | |
subject keywords | data preprocessing | |
subject keywords | data-driven analytics | |
subject keywords | data-driven knowledge extraction | |
subject keywords | data-driven methodology | |
subject keywords | data-driven methods | |
subject keywords | data-rich environment | |
subject keywords | database | |
subject keywords | feature extrac | |
identifier doi | 10.1109/EMBC.2014.6944578 | |
journal title | obotics and Automation (ICRA), 2014 IEEE International Conference on | |
filesize | 1642836 | |
citations | 0 | |
contributor rawauthor | Osa, T. , Abawi, C.F. , Sugita, N. , Chikuda, H. , Sugita, S. , Ito, H. , Moro, T. , Takatori, Y. , Tanaka, S. , Mitsuishi, M. |