March 14, 2024, 4:43 a.m. | Yi Ding, Su Zhang, Chuangao Tang, Cuntai Guan

cs.LG updates on arXiv.org arxiv.org

arXiv:2308.16207v2 Announce Type: replace
Abstract: Emotion recognition using electroencephalogram (EEG) mainly has two scenarios: classification of the discrete labels and regression of the continuously tagged labels. Although many algorithms were proposed for classification tasks, there are only a few methods for regression tasks. For emotion regression, the label is continuous in time. A natural method is to learn the temporal dynamic patterns. In previous studies, long short-term memory (LSTM) and temporal convolutional neural networks (TCN) were utilized to learn the …

anchor arxiv continuous convolutional neural networks cs.lg eeg emotion networks neural networks recognition space temporal type

Founding AI Engineer, Agents

@ Occam AI | New York

AI Engineer Intern, Agents

@ Occam AI | US

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Sr. BI Analyst

@ AkzoNobel | Pune, IN