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Disambiguation of "Yan, Jianzhuo"

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A depressive mood status quantitative reasoning method based on portable EEG and self-rating scale.

, , , , , and . WI, page 389-395. ACM, (2017)

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Yan Yan

Shanshan Yan

Americanization in China: an analysis of General Motors and its strategies in China. Uni Mainz, (2009)

Yan Xu

Untersuchungen zur Verleimung von Holz und Holzspanplatten mit UF-Leimharzen und PMDI. TU Braunschweig, (2009)

Yan Xu

Yan Zeng

 

Other publications of authors with the same name

Neuroimaging-ITM: A Text Mining Pipeline Combining Deep Adversarial Learning with Interaction Based Topic Modeling for Enabling the FAIR Neuroimaging Study., , , , , , and . Neuroinformatics, 20 (3): 701-726 (2022)A Probabilistic Method for Linking BI Provenances to Open Knowledge Base., , , , , and . BIH, volume 9919 of Lecture Notes in Computer Science, page 367-376. (2016)A depressive mood status quantitative reasoning method based on portable EEG and self-rating scale., , , , , and . WI, page 389-395. ACM, (2017)Analyzing Emotional Oscillatory Brain Network for Valence and Arousal-Based Emotion Recognition Using EEG Data., , , and . Int. J. Inf. Technol. Decis. Mak., 18 (4): 1359-1378 (2019)Terminology extraction in the field of water environment based on rules and statistics., , , and . CIPAE, page 144-147. ACM, (2020)The identification of Chinese named entity in the field of medicine based on Bootstrapping method., , , , and . MFI, page 1-6. IEEE, (2014)An EEG-Based Emotion Recognition Model with Rhythm and Time Characteristics., and . BI, volume 11309 of Lecture Notes in Computer Science, page 22-31. Springer, (2018)A Quantitative Analysis Method for Objectively Assessing the Depression Mood Status Based on Portable EEG and Self-rating Scale., , , , , and . BI, volume 10654 of Lecture Notes in Computer Science, page 223-232. Springer, (2017)Emotion Recognition from EEG Using Rhythm Synchronization Patterns with Joint Time-Frequency-Space Correlation., , and . BI, volume 10654 of Lecture Notes in Computer Science, page 159-168. Springer, (2017)NetFeatures-Transformer: Enhancing Brain Network Features to Classify Alzheimer's Disease., , , , , and . WI/IAT, page 503-507. IEEE, (2023)