Matches in SemOpenAlex for { <https://semopenalex.org/work/W4290564840> ?p ?o ?g. }
Showing items 1 to 89 of
89
with 100 items per page.
- W4290564840 endingPage "9017" @default.
- W4290564840 startingPage "9012" @default.
- W4290564840 abstract "Biological brain signals may be used to identify emotions in a variety of ways, with accuracy depended on the methods used for signal processing, feature extraction, feature selection, and classification. The major goal of the current work was to use an adaptive channel selection and classification strategy to improve the effectiveness of emotion detection utilizing brain signals. Using different features picked by feature fusion approaches, the accuracy of existing classification models' emotion detection is assessed. Statistical modeling is used to determine time-domain and frequency-domain properties. Multiclass classification accuracy is examined using Neural Networks (NNs), Lasso regression, k-Nearest Neighbors (KNN), Support Vector Machine (SVM), and Random Forest (RF). After performing hyperparameter tuning, a remarkable increase in accuracy is achieved using Lasso regression, while RF performed well for all the feature sets. 78.02% and 76.77% accuracy were achieved for a small and noisy 24 feature dataset by Lasso regression and RF respectively whereas 76.54% accuracy is achieved by Lasso regression with the backward elimination wrapper method." @default.
- W4290564840 created "2022-08-08" @default.
- W4290564840 creator A5007174699 @default.
- W4290564840 creator A5008041989 @default.
- W4290564840 date "2022-08-01" @default.
- W4290564840 modified "2023-10-14" @default.
- W4290564840 title "Human Emotion Detection with Electroencephalography Signals and Accuracy Analysis Using Feature Fusion Techniques and a Multimodal Approach for Multiclass Classification" @default.
- W4290564840 cites W2072787788 @default.
- W4290564840 cites W2289714406 @default.
- W4290564840 cites W2406223855 @default.
- W4290564840 cites W2507248126 @default.
- W4290564840 cites W2552144562 @default.
- W4290564840 cites W266504756 @default.
- W4290564840 cites W2791917003 @default.
- W4290564840 cites W2801785263 @default.
- W4290564840 cites W2885194508 @default.
- W4290564840 cites W2896370822 @default.
- W4290564840 cites W2901722731 @default.
- W4290564840 cites W2953214845 @default.
- W4290564840 cites W3120598210 @default.
- W4290564840 cites W3138409313 @default.
- W4290564840 cites W3145928148 @default.
- W4290564840 cites W334324399 @default.
- W4290564840 cites W4223481172 @default.
- W4290564840 cites W4223486107 @default.
- W4290564840 cites W4223525433 @default.
- W4290564840 doi "https://doi.org/10.48084/etasr.5073" @default.
- W4290564840 hasPublicationYear "2022" @default.
- W4290564840 type Work @default.
- W4290564840 citedByCount "0" @default.
- W4290564840 crossrefType "journal-article" @default.
- W4290564840 hasAuthorship W4290564840A5007174699 @default.
- W4290564840 hasAuthorship W4290564840A5008041989 @default.
- W4290564840 hasBestOaLocation W42905648401 @default.
- W4290564840 hasConcept C105795698 @default.
- W4290564840 hasConcept C119857082 @default.
- W4290564840 hasConcept C12267149 @default.
- W4290564840 hasConcept C136764020 @default.
- W4290564840 hasConcept C138885662 @default.
- W4290564840 hasConcept C148483581 @default.
- W4290564840 hasConcept C153180895 @default.
- W4290564840 hasConcept C154945302 @default.
- W4290564840 hasConcept C169258074 @default.
- W4290564840 hasConcept C2776401178 @default.
- W4290564840 hasConcept C33923547 @default.
- W4290564840 hasConcept C37616216 @default.
- W4290564840 hasConcept C41008148 @default.
- W4290564840 hasConcept C41895202 @default.
- W4290564840 hasConcept C52622490 @default.
- W4290564840 hasConcept C83546350 @default.
- W4290564840 hasConcept C8642999 @default.
- W4290564840 hasConceptScore W4290564840C105795698 @default.
- W4290564840 hasConceptScore W4290564840C119857082 @default.
- W4290564840 hasConceptScore W4290564840C12267149 @default.
- W4290564840 hasConceptScore W4290564840C136764020 @default.
- W4290564840 hasConceptScore W4290564840C138885662 @default.
- W4290564840 hasConceptScore W4290564840C148483581 @default.
- W4290564840 hasConceptScore W4290564840C153180895 @default.
- W4290564840 hasConceptScore W4290564840C154945302 @default.
- W4290564840 hasConceptScore W4290564840C169258074 @default.
- W4290564840 hasConceptScore W4290564840C2776401178 @default.
- W4290564840 hasConceptScore W4290564840C33923547 @default.
- W4290564840 hasConceptScore W4290564840C37616216 @default.
- W4290564840 hasConceptScore W4290564840C41008148 @default.
- W4290564840 hasConceptScore W4290564840C41895202 @default.
- W4290564840 hasConceptScore W4290564840C52622490 @default.
- W4290564840 hasConceptScore W4290564840C83546350 @default.
- W4290564840 hasConceptScore W4290564840C8642999 @default.
- W4290564840 hasIssue "4" @default.
- W4290564840 hasLocation W42905648401 @default.
- W4290564840 hasLocation W42905648402 @default.
- W4290564840 hasOpenAccess W4290564840 @default.
- W4290564840 hasPrimaryLocation W42905648401 @default.
- W4290564840 hasRelatedWork W2336974148 @default.
- W4290564840 hasRelatedWork W2985924212 @default.
- W4290564840 hasRelatedWork W3034132578 @default.
- W4290564840 hasRelatedWork W3174196512 @default.
- W4290564840 hasRelatedWork W3195168932 @default.
- W4290564840 hasRelatedWork W4288767684 @default.
- W4290564840 hasRelatedWork W4293525103 @default.
- W4290564840 hasRelatedWork W4327511089 @default.
- W4290564840 hasRelatedWork W4361733514 @default.
- W4290564840 hasRelatedWork W2345184372 @default.
- W4290564840 hasVolume "12" @default.
- W4290564840 isParatext "false" @default.
- W4290564840 isRetracted "false" @default.
- W4290564840 workType "article" @default.