From post

Emotion Recognition from EEG Using Rhythm Synchronization Patterns with Joint Time-Frequency-Space Correlation.

, , и . BI, том 10654 из Lecture Notes in Computer Science, стр. 159-168. Springer, (2017)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed.

 

Другие публикации лиц с тем же именем

Neuroimaging-ITM: A Text Mining Pipeline Combining Deep Adversarial Learning with Interaction Based Topic Modeling for Enabling the FAIR Neuroimaging Study., , , , , , и . Neuroinformatics, 20 (3): 701-726 (2022)A Probabilistic Method for Linking BI Provenances to Open Knowledge Base., , , , , и . BIH, том 9919 из Lecture Notes in Computer Science, стр. 367-376. (2016)A depressive mood status quantitative reasoning method based on portable EEG and self-rating scale., , , , , и . WI, стр. 389-395. ACM, (2017)Establishment of Risk Prediction Model for Retinopathy in Type 2 Diabetic Patients., , , и . BI, том 11976 из Lecture Notes in Computer Science, стр. 233-243. Springer, (2019)A EEG-based emotion recognition model with rhythm and time characteristics., , и . Brain Informatics, 6 (1): 7 (2019)A Personalized Method of Literature Recommendation Based on Brain Informatics Provenances., , , , , , , и . BIH, том 9250 из Lecture Notes in Computer Science, стр. 167-178. Springer, (2015)A Provenance Driven Approach for Systematic EEG Data Analysis., , , , и . BIH, том 9919 из Lecture Notes in Computer Science, стр. 190-200. (2016)A knowledge-driven approach for personalized literature recommendation based on deep semantic discrimination., , , , , и . WI, стр. 1253-1259. ACM, (2017)The identification of Chinese named entity in the field of medicine based on Bootstrapping method., , , , и . MFI, стр. 1-6. IEEE, (2014)An EEG-Based Emotion Recognition Model with Rhythm and Time Characteristics., и . BI, том 11309 из Lecture Notes in Computer Science, стр. 22-31. Springer, (2018)