This work is to design an emotional analysis system using Deep Neural Network based on electroencephalogram data. The data are processed using high pass filtering and removing DC offset method in the proposed system. Then the preprocessed dataset is constructed to analysis the impact of input data placement on recognition performance. In the experiment, the happy and neutral dataset are used to measure the proposed approach performance. The result shows that learning data by stacking one row at a time is better than learning data matrix sequentially.
|Title of host publication||Advances in Computer Science and Ubiquitous Computing - CSA-CUTE 17|
|Editors||Gangman Yi, Yunsick Sung, James J. Park, Vincenzo Loia|
|Number of pages||6|
|Publication status||Published - 2018|
|Event||International Conference on Computer Science and its Applications, CSA 2017 - Taichung, Taiwan, Province of China|
Duration: 2017 Dec 18 → 2017 Dec 20
|Name||Lecture Notes in Electrical Engineering|
|Other||International Conference on Computer Science and its Applications, CSA 2017|
|Country||Taiwan, Province of China|
|Period||17/12/18 → 17/12/20|
Bibliographical noteFunding Information:
Acknowledgements. This work was supported by Institute for Information & Communications Technology Promotion (IITP) grant funded by the Korea government (MSIP) (R0124-16-0002, Emotional Intelligence Technology to Infer Human Emotion and Carry on Dialogue Accordingly).
All Science Journal Classification (ASJC) codes
- Industrial and Manufacturing Engineering