Matches in SemOpenAlex for { <https://semopenalex.org/work/W2984356918> ?p ?o ?g. }
Showing items 1 to 82 of
82
with 100 items per page.
- W2984356918 endingPage "20" @default.
- W2984356918 startingPage "3" @default.
- W2984356918 abstract "EEG, Electroencephalography, is the acquisition and decoding of electric brain signals. The data acquired from EEG scans can be put to use in many fields, including seizure prediction, treatment of mental illness, brain-computer interfaces (BCIs) and more. Recent advances in deep learning (DL) in fields of image classification and natural language processing have motivated researchers to apply DL for classification of EEG signals as well. One major caveat in DL is the amount of human effort and expertise required for the development of efficient and effective neural network architectures. Neural architecture search algorithms are used to automatically find good enough neural network architectures for a problem and dataset at hand. In this research, we employ genetic algorithms for optimizing neural network architectures for multiple tasks related to EEG processing while addressing two unique challenges related to EEG: (1) small amounts of labeled EEG data per subject, and (2) high diversity of EEG signal patterns across subjects. Neural network architectures produced during this study successfully compete with state of the art architectures published in the literature. Particularly successful are architectures optimized for all (human) subjects, with evolution and training performed on a mixed dataset including all subjects’ data." @default.
- W2984356918 created "2019-11-22" @default.
- W2984356918 creator A5009349156 @default.
- W2984356918 creator A5059447087 @default.
- W2984356918 creator A5069914403 @default.
- W2984356918 date "2019-01-01" @default.
- W2984356918 modified "2023-10-18" @default.
- W2984356918 title "EEGNAS: Neural Architecture Search for Electroencephalography Data Analysis and Decoding" @default.
- W2984356918 cites W2009902427 @default.
- W2984356918 cites W2022637272 @default.
- W2984356918 cites W2026430219 @default.
- W2984356918 cites W2040084725 @default.
- W2984356918 cites W2126511896 @default.
- W2984356918 cites W2127817783 @default.
- W2984356918 cites W2130847623 @default.
- W2984356918 cites W2140413964 @default.
- W2984356918 cites W2270470215 @default.
- W2984356918 cites W2292901520 @default.
- W2984356918 cites W2551178936 @default.
- W2984356918 cites W2593744649 @default.
- W2984356918 cites W2741907166 @default.
- W2984356918 cites W2889245000 @default.
- W2984356918 cites W2963822470 @default.
- W2984356918 cites W2963919481 @default.
- W2984356918 cites W2964016673 @default.
- W2984356918 cites W2965658867 @default.
- W2984356918 doi "https://doi.org/10.1007/978-981-15-1398-5_1" @default.
- W2984356918 hasPublicationYear "2019" @default.
- W2984356918 type Work @default.
- W2984356918 sameAs 2984356918 @default.
- W2984356918 citedByCount "12" @default.
- W2984356918 countsByYear W29843569182020 @default.
- W2984356918 countsByYear W29843569182021 @default.
- W2984356918 countsByYear W29843569182022 @default.
- W2984356918 countsByYear W29843569182023 @default.
- W2984356918 crossrefType "book-chapter" @default.
- W2984356918 hasAuthorship W2984356918A5009349156 @default.
- W2984356918 hasAuthorship W2984356918A5059447087 @default.
- W2984356918 hasAuthorship W2984356918A5069914403 @default.
- W2984356918 hasConcept C123657996 @default.
- W2984356918 hasConcept C154945302 @default.
- W2984356918 hasConcept C15744967 @default.
- W2984356918 hasConcept C166957645 @default.
- W2984356918 hasConcept C169760540 @default.
- W2984356918 hasConcept C23123220 @default.
- W2984356918 hasConcept C40743351 @default.
- W2984356918 hasConcept C41008148 @default.
- W2984356918 hasConcept C522805319 @default.
- W2984356918 hasConcept C57273362 @default.
- W2984356918 hasConcept C76155785 @default.
- W2984356918 hasConcept C95457728 @default.
- W2984356918 hasConceptScore W2984356918C123657996 @default.
- W2984356918 hasConceptScore W2984356918C154945302 @default.
- W2984356918 hasConceptScore W2984356918C15744967 @default.
- W2984356918 hasConceptScore W2984356918C166957645 @default.
- W2984356918 hasConceptScore W2984356918C169760540 @default.
- W2984356918 hasConceptScore W2984356918C23123220 @default.
- W2984356918 hasConceptScore W2984356918C40743351 @default.
- W2984356918 hasConceptScore W2984356918C41008148 @default.
- W2984356918 hasConceptScore W2984356918C522805319 @default.
- W2984356918 hasConceptScore W2984356918C57273362 @default.
- W2984356918 hasConceptScore W2984356918C76155785 @default.
- W2984356918 hasConceptScore W2984356918C95457728 @default.
- W2984356918 hasLocation W29843569181 @default.
- W2984356918 hasOpenAccess W2984356918 @default.
- W2984356918 hasPrimaryLocation W29843569181 @default.
- W2984356918 hasRelatedWork W2043031633 @default.
- W2984356918 hasRelatedWork W2049312248 @default.
- W2984356918 hasRelatedWork W2293149528 @default.
- W2984356918 hasRelatedWork W2911559905 @default.
- W2984356918 hasRelatedWork W2912077104 @default.
- W2984356918 hasRelatedWork W2958904785 @default.
- W2984356918 hasRelatedWork W2976480173 @default.
- W2984356918 hasRelatedWork W2990829445 @default.
- W2984356918 hasRelatedWork W3097524063 @default.
- W2984356918 hasRelatedWork W3198983980 @default.
- W2984356918 isParatext "false" @default.
- W2984356918 isRetracted "false" @default.
- W2984356918 magId "2984356918" @default.
- W2984356918 workType "book-chapter" @default.