Matches in SemOpenAlex for { <https://semopenalex.org/work/W4313140903> ?p ?o ?g. }
Showing items 1 to 85 of
85
with 100 items per page.
- W4313140903 abstract "For brain doctors, knowing the type of seizures in patients with epilepsy is conducive to accurate treatment of patients. Although many researchers have done enough research on the prediction and detection of epileptic seizures, there is a lack of research on the classification of seizure types. Therefore, in order to classify the 8 types of epileptic seizures, this article proposes two ideas based on the fusion of multi-models of transfer learning. Extract the MAS features from the 22 montage combined channels, use reliefF for feature selection, and finally convert it to images. Use the following two transfer learning strategies:(1) Transfer learning multi-model feature fusion, (2) Transfer learning multi-model classification probability fusion. On the TUSZ data set of temple university school of medicine, use six pre-trained models of Alexnet, Googlenet, Inception-v3, Resnet18, Vgg16, and Vgg19. The results show that the proposed algorithm are better than the compared algorithms. The probability fusion strategy is adopted to obtain the best classification performance, classification accuracy and F1 score reaching 98.48% and 97.61 %, respectively." @default.
- W4313140903 created "2023-01-06" @default.
- W4313140903 creator A5012324763 @default.
- W4313140903 creator A5024611619 @default.
- W4313140903 creator A5070374842 @default.
- W4313140903 creator A5082905852 @default.
- W4313140903 date "2022-02-01" @default.
- W4313140903 modified "2023-09-24" @default.
- W4313140903 title "Multi-model decision-making seizure types classification based on transfer learning" @default.
- W4313140903 cites W1545302199 @default.
- W4313140903 cites W2117079761 @default.
- W4313140903 cites W2345279893 @default.
- W4313140903 cites W2394645992 @default.
- W4313140903 cites W2588128256 @default.
- W4313140903 cites W2592509339 @default.
- W4313140903 cites W2594644573 @default.
- W4313140903 cites W2901504266 @default.
- W4313140903 cites W2914978058 @default.
- W4313140903 cites W2920599647 @default.
- W4313140903 cites W2965277555 @default.
- W4313140903 cites W2976267777 @default.
- W4313140903 cites W2992904850 @default.
- W4313140903 cites W2995435729 @default.
- W4313140903 cites W3000002325 @default.
- W4313140903 cites W3026105287 @default.
- W4313140903 cites W3029452075 @default.
- W4313140903 cites W4233438293 @default.
- W4313140903 cites W4301347335 @default.
- W4313140903 doi "https://doi.org/10.1109/iscer55570.2022.00040" @default.
- W4313140903 hasPublicationYear "2022" @default.
- W4313140903 type Work @default.
- W4313140903 citedByCount "0" @default.
- W4313140903 crossrefType "proceedings-article" @default.
- W4313140903 hasAuthorship W4313140903A5012324763 @default.
- W4313140903 hasAuthorship W4313140903A5024611619 @default.
- W4313140903 hasAuthorship W4313140903A5070374842 @default.
- W4313140903 hasAuthorship W4313140903A5082905852 @default.
- W4313140903 hasConcept C119857082 @default.
- W4313140903 hasConcept C138885662 @default.
- W4313140903 hasConcept C148483581 @default.
- W4313140903 hasConcept C150899416 @default.
- W4313140903 hasConcept C153180895 @default.
- W4313140903 hasConcept C154945302 @default.
- W4313140903 hasConcept C15744967 @default.
- W4313140903 hasConcept C169760540 @default.
- W4313140903 hasConcept C177264268 @default.
- W4313140903 hasConcept C199360897 @default.
- W4313140903 hasConcept C2776401178 @default.
- W4313140903 hasConcept C2778186239 @default.
- W4313140903 hasConcept C2779334592 @default.
- W4313140903 hasConcept C41008148 @default.
- W4313140903 hasConcept C41895202 @default.
- W4313140903 hasConcept C81917197 @default.
- W4313140903 hasConceptScore W4313140903C119857082 @default.
- W4313140903 hasConceptScore W4313140903C138885662 @default.
- W4313140903 hasConceptScore W4313140903C148483581 @default.
- W4313140903 hasConceptScore W4313140903C150899416 @default.
- W4313140903 hasConceptScore W4313140903C153180895 @default.
- W4313140903 hasConceptScore W4313140903C154945302 @default.
- W4313140903 hasConceptScore W4313140903C15744967 @default.
- W4313140903 hasConceptScore W4313140903C169760540 @default.
- W4313140903 hasConceptScore W4313140903C177264268 @default.
- W4313140903 hasConceptScore W4313140903C199360897 @default.
- W4313140903 hasConceptScore W4313140903C2776401178 @default.
- W4313140903 hasConceptScore W4313140903C2778186239 @default.
- W4313140903 hasConceptScore W4313140903C2779334592 @default.
- W4313140903 hasConceptScore W4313140903C41008148 @default.
- W4313140903 hasConceptScore W4313140903C41895202 @default.
- W4313140903 hasConceptScore W4313140903C81917197 @default.
- W4313140903 hasLocation W43131409031 @default.
- W4313140903 hasOpenAccess W4313140903 @default.
- W4313140903 hasPrimaryLocation W43131409031 @default.
- W4313140903 hasRelatedWork W2374344280 @default.
- W4313140903 hasRelatedWork W3174196512 @default.
- W4313140903 hasRelatedWork W3210877509 @default.
- W4313140903 hasRelatedWork W4212852473 @default.
- W4313140903 hasRelatedWork W4225360065 @default.
- W4313140903 hasRelatedWork W4281382123 @default.
- W4313140903 hasRelatedWork W4293525103 @default.
- W4313140903 hasRelatedWork W4307883119 @default.
- W4313140903 hasRelatedWork W4308262314 @default.
- W4313140903 hasRelatedWork W2345184372 @default.
- W4313140903 isParatext "false" @default.
- W4313140903 isRetracted "false" @default.
- W4313140903 workType "article" @default.